Proceedings of the International Symposium for Production Research 2018

High productivity of parts manufacturing in industrial practice is closely related, not only to time efficiency, but also to the production of parts with high surface quality and considerable lifespan. Face milling is widely used for the efficient creation of accurately flat surfaces, for a large variety of part sizes and materials. However, determining the process parameters, which can lead to the achievement of all required conditions can be considered as a multi-objective problem. This problem can be sufficiently solved using suitable optimization techniques. In the present work, it is attempted to determine the optimum parameters for face milling of steel parts, in order to achieve minimum cutting forces and surface roughness, as well as maximum possible material removal rate. For that reason, after regression models are derived to correlate process parameters with cutting forces and surface roughness, an optimization process is carried out with two different optimization methods, namely Genetic Algorithm and Fireworks Algorithm and after the determination of the optimum process parameters, results concerning the efficiency of optimization algorithms are discussed as well.

In the paper examined was the influence of the cutting regime parameters on surface roughness parameters during turning of hard steel with cubic boron nitrite cutting insert. In this study for modeling of surface finish parameters was used central compositional design of experiment and artificial neural network. The values of surface roughness parameters R_a and R_t were predicted by this two-modeling methodology and determined models were then compared. The results showed that the proposed systems can significantly increase the accuracy of the product profile when compared to the conventional approaches. The results indicate that the design of experiments with central composition plan modeling technique and artificial neural network can be effectively used for the prediction of the surface roughness for hard steel and determined significand cutting regime parameters.

Watsons, established in 1841, is one of the world’s leading beauty and personal care industry with more than 6300 stores in 11 different markets. In addition to 280 Watsons’s stores, online shopping is also an alternative for Turkish customers.Usage of online tools and technologies for many different purposes has increased by 21st-century companies thanks to the great accessibility of the Internet. Therefore, due to current trends, many customers prefer online shopping. Among them, some of them are adding the products to their market basket but unfortunately; they are leaving the website without a purchase. This causes an important problem for most of the e-commerce retailers. In this context, research in e-commerce needs to determine the reasons that encourage them to buy as much as they need to understand the behaviours of consumers. However, it is difficult and complex to identify customer behaviour and the factors that encourage purchasing. Data mining techniques have become the focus of such analyses. This project mainly focuses on data classification approach to predict customer’s behaviour during the website visits of Watsons e-commerce channel.Based on the problem to predict e-commerce customers’ behaviour at the customers’ first entrance to the Watsons’s website, data classification approach is studied. The collected data from Watsons’ e-commerce site are analysed in the WEKA by applying different data classification algorithms. Two distinct data sets are determined; while dataset 1 includes all attributes, dataset 2 is created by considering the results of attribute selection algorithms. Both dataset 1 and dataset 2 are examined separately in WEKA software by using seven classifier. The data classification algorithm with the highest accuracy is selected. Some rules and trees are suggested to the company to predict future customer behaviours. To encourage the customers who leave the website of Watsons, rules are interpreted for suggestion.

With Industry 4.0, the Internet of objects, Internet services and cyber-physical systems have led to radical changes in every aspect of society. Artificial intelligence and intelligent systems that emerge together with technological developments are rapidly advancing towards becoming technologies that we use in almost every field of our lives and that are convenient for us. Thanks to these developments, computer systems, processor speeds and storage capacities have also increased cheaper computer systems and increasing processor speed and storage capacities have caused to be collected huge amounts of data. We have produce huge of data by the log files of WEB servers formed by the web sites we visit, blogs, photos, videos, texts etc. that we share through social media tools. Analysing increased diversity and volume of data and the result of this analysis is that more meaningful information and interpretation of the acquired knowledge is beyond what human competence and relational databases can do. At this point, data mining which allows large quantities of data to be transformed into meaningful and useful information, offers many advantages and facilities.Data mining enables the use of computer programs to find correlations and rules that provide meaningful, potentially useful future predictions from large amounts of available data. Nowadays, data mining is successfully applied in medicine, banking and insurance, telecommunication, marketing and customer service sectors. In the field of marketing, data mining techniques enable businesses to understand hidden patterns in their past history. Thus, it is possible to plan and realize new marketing campaigns in a fast and cost-effective manner, develop product and promotion activities for specific customer segments, price determination, customer preferences and product positioning, effect on sales, customer satisfaction, point-of-sale data analysis, supply and store placement optimizations as well as profits. This study is a review of literature to emphasize the importance of data mining and to identify applications related to data mining in digital marketing and customer relationship management. This work will enable data mining techniques to be used effectively and efficiently by businesses and to enable more ARGE activities in this regard.

Free-form surfaces have an important role in the mould and die industry. The accurate manufacturing of these surfaces are unimaginable without ball-end milling and application of CAM systems. The quality of the surfaces means not only the surface roughness, but the dimensional and geometric accuracy. The principles of GPS standards have increasing importance. The macro and micro accuracy depends on many parameters and circumstances, like tool geometry, cutting parameters, tool path properties and geometric parameters of the machined surface. The article presents the study of flatness and angularity error in case of 3D plane surface machined by ball-end milling.

With the development of industry, complexity of systems and equipment has increased extensively. This results in the introduction of many interdependencies (stochastic, structural and economic) among the components of systems. Neglecting these interdependencies, when planning maintenance actions, leads to undesirable outcomes such as prolonged downtime and higher costs. That is why a multi-component system approach needs to be taken into account in maintenance planning models. However, maintenance planning is a difficult task in multi-component systems because of their complexities. Energy production systems are notable examples of such complex structures consisting of many interacting components. Maintenance planning is extremely crucial for this sector since any unexpected malfunction leads to very serious costs. Therefore, the aim of this study is to formulate the maintenance problem of a multi-component dynamic system in thermal power plants focusing on system reliability prognosis. Bayesian networks (BN) are probabilistic graphical models that have been extensively used to represent and model the causal relations. A dynamic Bayesian network (DBN) is an extended BN which has a temporal dimension. We propose to use DBNs to prognose the reliabilities of components and processes of a dynamic system in a thermal power plant and show that this representation is efficient to model the interdependencies and degradations in such a system.

Through the last decade, Industry 4.0 has been a transformative wave of change that affects organizations in several aspects. One of the most crucial elements in this context is the organizational adoption for upcoming changes. In particular, recent literature involves several maturity models where various challenges were discussed in several dimensions/pillars. Such models provide assessments that identify critical aspects that require more intensive efforts for development. However, a more holistic approach that signifies the overall organizational readiness has been scarce in previous research. This study presents an analytical model that provides an overall estimation of organizational readiness to Industry 4.0. This model is a three-stage model. The first stage involves the selection of relevant criteria by high/mid-level decision makers in organizations to be assessed from the criteria pool based on the KPIs discussed in the literature. In the second stage, the model uses decision makers’ pairwise comparisons for relevant criteria and determines the importance weights of these criteria using the AHP (Analytic Hierarchy Process) method. In the last stage, decision-makers evaluate the level of organizations with the group decision under relevant criteria. The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method with predetermined ideal and negative ideal solutions is applied using these evaluations to reveal the readiness level of organizations to Industry 4.0. The model is applied to a company operating in the apparel industry in Turkey, and organizational readiness level of the company to Industry 4.0 is evaluated.

Recently effective planning and management of maintenance activities have gained great importance. Although proactive maintenance approach is preferred against reactive maintenance approach in some highly critical systems, it is inevitable to give up the latter one because of the probabilistic nature of faults. Hence, reactive maintenance is still widely applied. Therefore the aim of this study is to develop an effective reactive maintenance strategy for a dynamic system consisting of four components. Components are hidden and degrading over time. However it is possible to receive partial observations about the condition of the system. One can replace components at any time period. Our aim is to minimize the total number of replacements in a given planning horizon. We propose several approaches within the framework of reactive maintenance for this system and compare their performances by simulating these using Dynamic Bayesian Networks.

There have been different evaluation criteria which effect the decision making process. The methods that help the decision making process by taking into these criteria account together are called multi criteria decision making methods. Electre (Elimination Et Choix Traduisant la Realite) method is one of them. Within this study, hydraulic bending machines for profile, pipe and beams will be compared according to shaft diameters, rolls diameters, working speed and motor power evaluation criteria with the help of Electre method.

This study aims at evaluating of machine alternatives that the companies need for metal forming with MOORA method. Evaluation criteria have been determined as engine power, approach speed, working speed and return speed. Preference ranking of 61 different models have been analysed by taking into account all of these criteria together from the viewpoint of the companies.

With rapid advancements in industry, technology and applications, many concepts have emerged in the manufacturing environment. It is generally known that the term ‘Industry 4.0’ was published to highlight a new industrial revolution. Maintenance is a key operation function since it is related to all the manufacturing processes and focuses not only on avoiding the equipment breakdown but also on improving business performance. Monitoring of manufacturing systems for maintenance helps to identify equipment condition and failures before equipment breakdowns. Total Productive Maintenance (TPM) is widely used maintenance strategy to gain a competitive advantage in the industry. In this context, this paper focuses on the incompletely perceived link between the Industry 4.0’s key technologies and TPM. Conjoint analysis, which is a multi-attribute decision making method based on experimental design, is implemented to quantify the impacts of Industry 4.0’s key technologies on pillars of TPM. Moreover, interaction between key technologies of Industry 4.0 and pillars of TPM demonstrates several opportunities for achieving synergies thus leading to a successful implementation of future interconnected smart factories. The major contribution of is to provide a guideline and technology roadmap for investment decision for industries that are under the transformation phase towards future smart factory and offers a space for further scientific discussion.

Today’s retail companies are facing with many different criteria in choosing the software they use to manage their processes. The choice of appropriate software is a multi-criteria decision-making problem that requires process managers to come together with multiple factors as well as with different decision makers. In this study, the problem of choosing process management software for a retailer operating in the textile sector is discussed. The main problem in existing software used in the company’s process management department is that it does not cover all process flows causing lack of communication with other softwares. With this study, it is aimed to reduce time loss in operations by selecting a software that combines processes in one system. Thus, in all departments, there will be a unified and single reporting system for real-time analysis of statistics and better cooperation. In this study, the Analytic Hierarchy Process (AHP) and Fuzzy TOPSIS approaches are presented for this multi criteria decision making problem. In the first step, the AHP implementation and the pairwise comparisons taken from the seven decision makers determined the importance weights of the integrated decision criteria. In the second step, the Fuzzy TOPSIS method is carried out for the selection of the best software with the quantitative and qualitative evaluations of the decision makers.

Multi Criteria Decision Making (MCDM) is a process to decide the best possible ranking between alternatives. In fuzzy sense, fuzzy MCDM methods aim to get closer the best alternative. Interval valued intuitionistic fuzzy sets can be applied in MCDM and they form many fuzzy methods. One of them is MULTIMOORA which tries to deal with lessening incertitude options. MULTIMOORA method becomes important because of its usage compared to other MCDM methods. In this paper, the data in which Baležentis and Zeng (2013) studied is used and GIFTNOWGA operator which Baležentis and Zeng studied is replaced by Einstein operator to investigate how choosing different operators affect the final ranking of alternatives.

Nowadays sustainability is one of the most important topics in the developing world. Sustainability might include three main aspects in which one of the dimensions is environmental sustainability. Due to changing conditions of the world, decreasing natural resources and increasing needs of public conscience towards environment, not only environmental sustainability conscience, but also the word “green” gain importance. Furthermore, in healthcare and construction areas, green constructions, which mainly are green buildings and green hospitals, are outstandingly taken into consideration. Even if green hospitals are sub-buildings of green buildings, they have a lot of similarities and differences. The aim of the study is to give a general view by comparing green hospitals and green buildings and have a perspective about the main features of green buildings and green hospitals. In this study, two different analytic hierarchy processes are applied to compare green hospitals and green buildings and to have a perspective about which features of green buildings and hospitals are the most crucial. Besides, as a different spectacle, this study will investigate of which factors should be encouraged to have a better quality of green buildings and hospitals.

This article has presented the results of the analysis regarding the size and shape accuracy also selected spatial parameters of the surface of ducts that were made with the use of various processing strategies. The milling process of passage ducts was performed at a DMU-50 vertical processing center with the use of a Guhring 3309 carbide cutter with diameter of 8 mm. The cutting tests involved making seven ducts with the size of 12 × 60 × 10 mm in a semi-finished product made from aluminum alloy type 2017. The analysis of the size and shape accuracy of the made ducts was performed with the use of the ZEISS Prismo Navigator coordinate measuring machine. The analysis of the surface was conducted on a TalSurf CCI optical profilometer.

A stand for durability testing of rolling bearings is presented in this paper. The project assumptions of the stand, mechanical construction and architecture of data acquisition and analysis system (hardware and software) are described in this paper. Finally, there are conclusions about stand’s capabilities included. The device allows is capable of testing the running characteristics of bearings under varying test conditions and loads, speeds, lubrication conditions and temperatures. This stand provides precise measurements and autonomic work which is necessary in long-term researches. Compact construction of the stand containing overload protection system and automatic turn off system, activated after exceeding limit values of operating parameters or diagnostic signals, allows autonomic work without frequent human supervision. The data obtained from the stand will be used in future researches. In addition, they allow to test the service life under the set operating conditions.

The paper present test results of a measurement surface texture of models manufactured by FDM (fused deposition modeling) technology. The material used for constructing sample models was a structural material - ABS P430. A Dimension 1200es machine by Stratasys was used for the construction of the models. The process parameter, of which the impact on the quality of the surface texture was analysed, was the model orientation on a virtual building platform. A Form Talysurf PGI 1230, Taylor Hobson contact profiler was used for the measurements, and the test results were compared with the results obtained during the measurements with an optical profilometer.

Frictional moment is one of the parameters that determine the time and quality of working bearings. Therefore, it is important that it is possible to accurately predict the value of the frictional moment. This article analyses the impact of the track waviness on the frictional moment. In the research, a correlation analysis of selected wavelength parameters and frictional moment was performed and frictional moment. Those parameters wavelength are not included in the models used to determine the theoretical value of the frictional moment.

The paper studies the possibility of application of a two-dimensional wavelet transform to analyse surface texture signals. The tests were directed at determining the impact of wavelet transformation parameters in the scope of using the wavelet analysis to separate the constituents of measured surface irregularities. The surface roughness signals obtained as a result of the Gaussian filter application and after wavelet decomposition were compared. Based on the obtained results, it was concluded that a wavelet transform may be used to separate 3D surface texture constituents.

The advantage form no interference in the measurement system causes that Doppler laser vibrometers could be used in combination with other contact sensors, and also very helpful for tests determining the metrological properties of rolling bearing vibration measurement systems. Therefore, it is necessary to study problems related to the impact of the laser beam on the external surfaces of the tested bearings, as well as to determine the scope of use of laser vibrometers in the study of bearing vibration measurement systems.

Miniaturization offers two options to come closer to the micro and nano scale: bottom-up or top-down. Each method has its own and unique benefits, although in practice the top down approach is more common, as most companies find the top down approach to be the simpler method. So can similar processes use the top-down method to reduce the size of a precision gear? In our first attempt, a plant gear similar to a harmonic drive gearbox is to be made it smaller, lighter and cheaper using a 3D printing method. Then industry 4.0 lab is used to see how the production process meets I 4.0 requirements. Working on RP4 gears, which have been patented by TU Vienna, nearly no backlash can be expected due to the use of radial ball bearings. If the RP4 gear is miniaturized to one tenth of the original size, functionality issues can be expected because of the smaller auxiliary parts, and no matching radial ball bearings are available in the official market. Thus, our focus is on redesigning the existing gear which will have the same functionality. Furthermore, the geometric tolerances of the existing are compared with the new gears produced by additive manufacturing to understand the functional and metrological problems. Possible solutions may lie in modifying those bearings or in creating a new generative design instead.

Offset printing is the method for producing commercialized printed media as newspapers and magazines. There are various factors contributing to the overall print quality such as; paper, ink pigment penetration, ink water balance, hygiene of environment, air temperature and humidity. Moreover, quality control is still operator dependent process where the operator is responsible for the visual checks of the printed material. One of the major checks applied is the correct registration of the plates in order to have a sharp image. The misregistration check may require more than one iterations creating setup time variation. Consequently, this highly time consuming setup takes considerable amount of time, especially in low circulation amounts. In this study a novel method called Cross Mark Coordinate Determination and Automatic Registration (CMCDR) is proposed for setup time reduction. CMCDR is based on x and y intensity profiles of registration marks and applied in a printing shop for automatic registration. For this purpose a traditional registration cross for overlapped color components (CMYK) as well as one registration cross for each individual color component is used to determine misclassification error. Using x and y intensity profiles of individual color component to determine misregistration errors and corrections of misregistrations are reduced with only one iteration.

Unmanned Aerial Vehicle (UAV) also known as drone implies to a pilotless aircraft, a flying machine without a human pilot onboard. Most recently, UAV is widely used in civil and military based applications such as remote sensing, scientific research and aerial surveillance. In this study, a special drone with control mechanism was designed and developed. The main purpose was to build an efficient and user friendly remote control system to fulfill the deficiency of advanced control units. A graphical user interface (GUI) with touch screen was designed and implemented for motion control. The control unit had capability to reach each motor on UAV separately via duplex communication and control their speed precisely with pulse width modulation method (PWM). As a result of this study, a simple and efficient UAV system was developed that has ability to display and analyze the collected field data. An agricultural robot developed will be integrated with the proposed UAV in order to control the agricultural field operations.

The paper presents a design basis adopted for the construction of a test bench for rolling bearing durability testing. This article presents preliminary engineering requirements and the design of a special test rig for the examination of rolling bearings without the necessity of mounting the bearings in a specific machine component unit. The rig testing is widely used in consideration of numerous good points of such a method. The on test rigs consists in reproducing as accurately as possible the real conditions of operation of the bearings when mounted in the device for which they are intended. The device allows is capable of testing the running characteristics of bearings under varying test conditions and loads, speeds, lubrication conditions and temperatures. In addition they allow to test the service life under the set operating conditions.

Remote data acquisition and monitoring have an important role for industry and home appliances to provide real time status of monitored constituent. Nowadays, Wireless Sensor Technology (WST) is one of the common topics for research and development. Advanced technology continuously increases abilities of components related to these types of systems while reducing their sizes and costs. In this study a real-time wireless temperature data monitoring system including four nodes to acquire temperature based data and one base station to monitor these collected data was developed. Communication between remote terminal units (RTU) and base station was implemented using Radio Frequency (RF) transceivers. Time-division multiple access (TDMA) method was established to provide sequential access to each RTU. Developed system could be adequate for continuous communication and also it was able to support additional RTUs. Laboratory tests were conducted to demonstrate developed system’s functionality. During these tests, RTUs placed in standard refrigerators were used to observe temperature differences using wireless sensor network (WSN).

In recent years, many industries have designed their production in accordance with the principles of lean production, increased flexibility and achieved great success in productivity. Currently, production is facing on a new breakthrough. Virtual Reality is a promising new medium that’s changing the way we approach 3D Modeling. It allows artists to immerse themselves in a virtual workspace where they can construct, carve, and paint their visions like never before. Also, VRP is definitely a requirement of market, because the Comprehensive design by VRP carry with usability, salability, maintainability, acceptability, manufacturability and availability. Efficiency contribution of the VRP reduces the time to time market, reduces innovation risks and increases the innovation head start. What is virtual prototyping. Virtual prototyping is the first step for the technology and unified technology acceptance. Extended Technology Acceptance model, Technology life cycle and competitive position, technologies portfolios are important parts of the product developer. The best examples of virtualization include the digitization of product development, for example through the use of 3-D models and the development of data-based product models for the various value-added processes. The digitization of process designing is such as CAD-3D simulation, augmented reality, 3-D user interface, stereoscopic desk top VRP, modelling. In this study, these topics are investigated comprehensively and the future suggestions on the industry 4.0 is presented for the complex product development.

More recently, the industrial CT equipment is used not only for non-destructive analysis but to perform geometrical evaluations. The three dimensional, optical dimensional measurements made by CT are popular because the measurement time is much shorter than in case of traditional 3D measurement machines, furthermore the inner geometries can be determined by non-destructive manner. In this article the design and measurement plan of an aluminium test cube by industrial CT are described and the evaluation of the measurement data are presented.

Additive manufacturing (AM) is a layer-by-layer manufacturing method from 3D digital model, without using molds, fixtures and tools. This rapidly developing technology provides opportunity to obtain customized products with complex geometries, freeform shapes, internal cavities and lattice. However, lack of quality insurance procedures and policies are the gaps waiting to be filled. Precision metrology is the key factor for inspection of dimensional tolerances and surface quality of AM manufactured parts. For filling these gaps precision measurement techniques have to be developed parallel with additive manufacturing technology. With the 4th industrial revolution it would be possible to inspect the produced parts during manufacturing process by using in-line measurement techniques. Coordinate metrology (CMM), optical metrology and industrial computed tomography (x-CT) are primary precision measurement techniques used for quality control of the AM parts. In this study an application of the optical metrology for AM parts are given and measurement steps are investigated in terms of controlling dimensional deviations.

Measuring instruments based on contact methods are commonly used in industrial, as well as laboratory conditions for the evaluation of geometric structure of the surface elements of machine parts. One of the flaws of such measuring systems is the risk of damaging a measured surface due to the contact with the measuring tip. The paper discusses research aimed at evaluating the impact of a stylus profiler measuring tip passage on the condition of the surface layer of samples made from three different materials, i.e. C45 steel, EN-AW-2017A aluminium and Vero White liquid resin. The tests involved thirty measurements of surface roughness of the selected samples and evaluating the changes in the basic roughness parameters due to the passage of a profiler measuring probe. The condition of the analysed samples was evaluated after the roughness measurements using a Talysurf CCI non-contact profilometer. The tests demonstrated that a multiple passage of a stylus profiler measuring tip influences the change in the measured surface roughness parameters. Moreover, the roughness measurement on the surface of a sample made from EN-AW-2017A aluminium caused a clear scratch.

The Industrial Revolution, which began with the invention of steam-powered machines in the 18th century, caused a great resonance in the world and greatly affected the fate of mankind. Thanks to day-to-day technology, the rapidly developing manufacturing sector has overtaken the third generation and is now entering into its the 4. decade. As mentioned above, the industrial revolution, which started with steam power, then took advantage of the electrical power, and later, with the development of the information industry, the electronic digital revolution took its first step. Today, the 4th Industrial Revolution is called Industry 4.0.Industry 4.0 consists of many sub-headings. When this technology is used in the manufacturing industry, it takes the name of the Internet of Things (IoT), similarly when it is used in the service sector it is also called the Internet of Services (IoS). The fact that objects, services are in a single network, and that they can be managed from a centralized system, contributes positively and brings a number of threats as well. A number of precautions are taken against the cyber attack that may occur in this direction and studies are being conducted on this subject.Generally speaking, the factories that switch to Industry 4.0 technology will enter into a modular system, which means that the machines that are used in the factory will communicate on the internet and work without human power. In other words, the objects will be moved to the virtual platform, and the business will be made smart by being able to be controlled from the virtual platform. This will lead to a reduction in time loss, a reduction in costs, an increase in productivity, and an improvement in business performance. The aim of this study is to understand how Industry 4.0 that is spreading around the world rapidly yet mainly started by large businesses in Turkey is perceived in Konya which has intensive industry in Turkey. In this context, the exploratory research method was used. During the implementation phase, a questionnaire was prepared to evaluate the approaches of enterprises to Industry 4.0, and a face-to-face interview was conducted with two business managers. Within the scope of study, it is aimed to encourage enterprises to adapt the technological age introducing the 4. Industry Revolution and also to contribute to the academic literature about Industry 4.0 which is newly being researched in Turkey.

Over the past years, Enterprise Resource Planning (ERP) systems have become an essential business driver with its main features such as modularity, real-time data accessibility and sharing an integrated database on the way to Industry 4.0 Many companies have utilized the advantages of integrated solutions of ERP systems offered by multinational corporations. Nowadays, ERP systems have been widely adopted in specially developed countries as well as developing countries. In developing countries, companies usually use national ERP systems instead of foreign-based ERP systems. However, ERP vendors, consultants have offered different global ERP templates containing their multi-language and high qualified customization options, but also have some cultural adoption problems which may exist during the implementation of ERP systems. Thus, ERP systems face many challenges in, especially developing countries including cultural issues. This study focuses on cultural issues in ERP adoption which might be different across cultural contexts. It is aimed to assess the impact of cultural aspects in the implementation of ERP systems via holistic view by using Hofstede’s cultural dimensions (power distance, individualist/collectivist, uncertainty avoidance, etc.). Studying such aspects may provide guidelines for the success of ERP system adoption in a global perspective.

In recent years, ERP systems have provided a competitive advantage as well as their increasing significance for companies in a rapidly globalizing world. Accordingly, changing technologies and trends in the world are closely followed in Turkey, too. Traditional products have started to give their ways to cost-effective products, mainly provided by rental models via cloud technologies. This transformation process is first being developed and popularized by big players, and then a range of local solutions have arisen. Mobile technologies and IoT solutions via cloud technologies also positively drive this change. There are different types of ERP systems such as traditional, cloud-based, hosted or on premise. Cloud-based ERP solutions are becoming more attractive with increasing features. Currently, the overall resources of companies can be integrated through cloud-based ERP. Therefore, many companies have adopted these systems. There is a range of vendors offering ERP solutions in Turkey. Most of these vendors introduce themselves as successful players on the progress of the ERP sector in Turkey. The present study attempts to analyze the cloud-based ERP solutions of these vendors and to find out the pros and cons of cloud-based ERP systems in Turkey. For this purpose, interviews, as common qualitative tools, will be conducted on convenient samples to collect data and to gather and to explore insights as well as perceptions of cloud consultants and project managers of ERP vendors. Then, obtained data will be identified and clarified for SMEs which are concerned with ERP systems. The findings of this study are aimed to provide meaningful insights of consultants and project managers of cloud-based ERP systems. The present study is expected to share experiences on the progress of the ERP sector as well as the cloud-based ones in Turkey towards the way to Industry 4.0. Finally, some recommendations will be given to SMEs to support them on their journey towards cloud-based ERP.

This article is focused on development of mechanism for easy accessibility seat for disabled people, especially for easy getting in and out of the vehicle (Volkswagen UP 3 door version). Mechanism is easily adaptable for any other vehicle of similar type. Kinematics of mechanism is especially designed for seniors and people with lighter moving problems driving around town in a small city car. Project was released.

The biomedical techniques have been developed over the last decade rapidly through digitalisation, modern devices and sophisticated measurement equipment. In order to meet the demand in functionality of the non-technical structures, combined challenges of biological chemical and mechanical reactions need to be studied in detail. This study focuses on the latest developments with applications in modern production techniques and sophisticated measuring devices in strategic directions of tissue and dental implants. 3D printing of non-technical structures such as dental implants and scaffolds for tissue engineering are being researched. Computer tomography and techniques are applied to create and evaluate the shape of these structures targeting high accuracy and functionality. The digitalisation and modelling of the structures through advanced equipment are defined as key points in transition to the Industry 4.0 concept in biomedical technologies.

The current possibilities of production automation allow the manufacturers of machine tools to consider new possibilities of acquiring the necessary information on the ongoing production process and the suitable ways of their use. This paper presents the potential of the applications for data acquisition from the control systems, implementation of the sensor systems into the production process, big data processing and development of a knowledge base allowing for efficient decision-making of the operator and planning of production tasks or maintenance of the machine, as well as the risks associated with remote access to machines within production digitalization in connection with the elements of Industry 4.0.

The Fourth Industrial Revolution or Industry 4.0 is the name of recent digital transformation era. This transformation is conducted to improve digital operational abilities, perform collaboration and integration in the ecosystem, manage data, and develop cyber security. Industry 4.0 has become a very popular issue recently, but there is lack of understanding about its impact on real practices and the barriers expected to be encountered in the near future. Under the uncertain environment of digitalization, the companies need an evaluation method to define their strengths and weaknesses in the adaptation process. In this study, the methodologies for evaluating Industry 4.0 readiness level of companies are reviewed, and one of the most applicable methods is utilized for evaluation of three leading Turkish companies from different industries. In addition, the awareness of companies is also evaluated in terms of operational and socio-economical perspectives. Little research has been conducted on (1) reviewing the opinions of the companies on the socio-economic effects of Industry 4.0 and (2) evaluating Industry 4.0 readiness in developing countries. This study contributes by evaluating three cases dealing with the perceptions, awareness, and readiness of the Turkish companies in Industry 4.0 adaptation process. The result of the research shows that companies failing to develop road maps and new workforce planning strategies in the adaptation process under the uncertain environment of Industry 4.0 prefer to be the follower rather than the pioneer.

Today the industry is revolutionizing into a new era with the total integration of all elements of the production through digitalization and establishing communication between each other. This new revolution is named as “Industry 4.0”. Turkey is categorized as a developing country in terms of economy and Turkish economy is ranked at 17th place in world Gross Domestic Product (GDP) ranking. The country’s economy met the expectations and reached 7.4% GDP growth in 2017 while worldwide average growth was 3.6%, and developing countries had the average of 4.6%. Turkish government encourages enterprises to keep up with industry 4.0, and KOSGEB (Small and Medium Sized Enterprises Development Organization) is supporting the SMEs with various programs. This can be seen as an opportunity for Turkish industry to catch the trend and increase its growth rapidly. And at this point the exact knowledge of the current situation is crucial. Small and Medium Sized Enterprises (SME) has the 99.8% of the total according to Turkish Statistical Institute (TÜİK). Hence, this project is initiated to identify the current situation of SMEs of Turkish industry. A comprehensive questionnaire is prepared to find out the readiness and requirements of the SMEs for Industry 4.0 transformation. This questionnaire is applied to SMEs operating in Marmara Region of Turkey. The outcome of the research shows a scorecard for the SMEs in terms of technology usage, readiness to Industry 4.0, and also increased their awareness on the concept and the importance of the new era. The future studies are continuing as a second phase of this research in order widen the research to all regions of the country, and to develop the transformation capabilities of the selected enterprises.

Development and integration of advanced manufacturing technologies in the so labelled Industry 4.0 hold the promise of benefits as well as challenges. The need for addressing challenges lay out the requirement for the measurement & law & quality fundamentals. Industry of the future defined with guidelines will not only provide the added value in industry but moreover for humanity by means of a systems approach in the new era of industry. In this study, we establish the concepts and activities required as pillars of “Justicia/Justice” by means of measurement & law & quality in advanced manufacturing operations. A universal basic model will highlight main factors and increase insight in key success players integrating future plans in a meaningful way.

This article deals with the performance of modern sensor systems for autonomous vehicles. The examined automobile was equipped with state-of-the-art sensor technology and provides a solid basis for the further close-to-production development of the increasing requirements for environmental recognition. With regard to Industry 4.0, too, parallels can be deduced, since progressive networking between cars and infrastructure is assumed by the fact that the IoT (Internet of Things) is being expanded in both areas.The following publication evaluates the performance of vehicle-specific methods and sensors in modern vehicle assistance systems under real driving conditions. In addition, a high-resolution vehicle dynamics measurement was performed on a partially automated test vehicle. The test results show that for good weather conditions and good road infrastructure, there is no discernible difference in driving behavior between manual and partly autonomous operation. Finally, a route model was created based on simulations using MATLAB SIMULINK. The deviation of the simulated from the measured lateral acceleration is discussed.

Smart factory has become increasingly important in the last years as an indispensable manufacturing model of the future. In this context, studies on the development of technologies in the field of smart factory systems intensively continue in the world. Turkey is also trying to contribute through national grant mechanisms to encourage technology development efforts in this area. In this study, the situation of smart factory system technologies in Turkey has been explained. By examining the academic studies and by carrying out a questionnaire study to companies and academicians studying in this field, suggestions are made about which of the smart factory system technologies should be given priority to gain momentum in this field.

By the introduction of Industry 4.0 technologies and tools, manufacturing companies and especially SME (Small and medium sized companies) from supplier tiers of main manufacturing value chains faced the challenge of uncertain environment and lack of methods in making effective technology identification, prioritization and selection in accordance with their productivity and effectiveness improvement needs. Especially from a developing country perspective, being decision makers in the user side of Industry 4.0 value chain had been in a quest for decision making models that can be used in technology investments for Industry 4.0 technologies. However, due to the fact that, balancing potential benefits, barriers/challenges of Industry 4.0 tools with current or potential improvement needs in manufacturing systems require high level of knowledge and expertise both in manufacturing and Industry 4.0 technologies, most of the researches which focus on few pillars of the problem remained insufficient as they lack interdisciplinary and qualitative approaches. Especially for technology-dependent and follower countries such as Turkey that has limited resources and strict constraints, previous researches with proposed decision making models on digital transformation are very limited. In this context, this study proposes a multi-dimensional and hybrid technology evaluation methodology for technology selection on Industry 4.0 technologies that covers technological issues, competitive competencies and managerial pillars together. By combining the pillars of technological tools, benefits and challenges of their usage in manufacturing industry, the proposed model utilizes multi -criteria decision support model, namely AHP, a Needs Analysis framework based on Quality Function Deployment approach. Data collected via interviews and survey, the qualified participant having manufacturing excellence are preferred. Outputs from the model is expected to serve decision makers in SMEs of manufacturing industry for technology selection and use case scenario generation for the best and appropriate strategy.

Today, people are more aware of the importance of Industry 4.0, which increasingly influences the decisions of service or product innovation. Meanwhile, managers take much more care of both this trend and permanence in the market depending on the ability to innovate services and goods that ensure care of sustainable innovation. Because, undoubtedly, innovation must be taken into consideration as a long-term capability. Hence, the organizations have the advantage to enable translation of primary goods/services into higher value-added products. In the direction of this information, this paper was completed in the shadow of Industry 4.0., which is called “big data box”. This study, showing the triple interaction, includes various kinds of minor innovation projects, like many branches of a tree. However, every branch in this big data box tree serves to the same target. The research also extracts more value from the inputs used in process, which in turn, improves productivity and increases the capacity of establishment to meet needs of consumers. With the target of proofing the implementation of this big data box was completed in a foundation in health field, “A corporation”, having triple collaboration of three main drivers; Industry, university and government. Therefore, this paper has shown that the innovation performance of the “A” corporation keeps going further by means of big data. In addition to this, it should not be forgotten that organizational climate was affected in a positive way, too. Big data box, evaluating the innovation performance, was conceptualized and studied as a phenomenon linked to the activities of research&development done by technical staff in “A” corporation. It’s related to form a smart memory, setting light for the future projects. After completing this study, innovation ideas and new collaboration models between Industry and university can easily be formed.

At the present time, the demand of air transportation has been increased by global population growth and the rise of middle class in developing countries, economic progress of international trade, and upward trend in sensitivity towards pace and security. This situation consistently prompts to airline businesses on the subjects that are increasing the productivity on their operational activities and developing new business models. While Internet of Things (IoT) which is rapidly spreading around the world at this point is implemented with the dream of that everything would be bigger, faster and cheaper; the reflection of those dreams can affect on aviation industry. Studies of IoT in aviation industry are able to help aviation industry provide benefits namely provide customer satisfaction growth with higher comfort and productivity growth on supply chain activities, reducing the cost with decreasing of human related accidents, developing security activities, decreasing travel time on aviation.There is a great deal of applications regarding IoT in aviation industry, however, research and academic papers are not adequately conducted in the field. Within this scope, the aim of the study is to examine theoretical aspects of IoT applications in service sectors and analyse IoT tools in process of production of services used by airline and airport operators. Heuristic approach as one of the applied research methods will be used in this study.In the first part of the study, the theoretical research on the definition, benefits and losses of IOT is given. In the second part, IOT application areas are examined. In the final section, we have included innovations in civil aviation that will serve as examples of IOT and can be regarded as innovations around the world.

The ultimate objective of manufacturing industries is to increase productivity with high quality. At present, many manufacturing companies are facing problems such as high quality rejects, high inventories, long lead time of production, high costs of production, and inability to cope with customer orders. They have been trying to reduce the total cost and wastes across their supply chain to remain competitive in the expanding global market. Hence, a collection of reliable tools and techniques are vital for decreasing costs and wastes and for providing effective services for customer demands. One of these techniques is Kaizen. Kaizen which means continuous improvement according to the principle of excellence which is a lean management model that envisages the participation of all managers and employees in businesses. This model predicts that continuous improvement should be made in every aspect of business and social life. Kaizen studies provide great results with improvements in small steps. As a result of Kaizen improvements, innovative results with small but sure steps have been achieved. In this context, Success is achieved by placing process standards and discipline with plan, do, check, take measure cycle that Kaizen in the business management system.In this study, Kaizen studies was applied in two areas in a large flour factory. First, Conveyor Band System Development Project. Second one is Final Finished Product Loading and Stacking Project. In this context, Conveyor Band System Development Project; reviewing and analyzing the existing situation, proposing and implementing improvement, and controlling and standardization the results. In the Final Finished product and Stacking Workers Project, the examination and analysis of the existing situation, the proposal and implementation of improvement and the checking of the results and the rules of procedure were investigated. As a result of the research, a general evaluation is made about the Kaizen applications in the flour factory and suggestions are presented.

Rapid developments in information communication technologies have caused radical changes in all areas of society. This change has led to changes in the lifestyles of individuals and of the ways and modes of doing business of enterprises. It is possible for businesses to be able to survive and compete with the right product, at the right place, the lowest cost and meeting customer demands and expectations. Increased competition, customer orientation resulting from changing customer expectations and demands have also changed the manufacturing systems and methods. Businesses have had to use sustainable flexible production methods and techniques which quality-focused, cost-effective and the least wasteful in order to meet customer demand expectations. Identification of problems, prevention of mistakes, identification and solving of related problem areas and high preparation times are important problems in manufacturing. Automatically detecting faults and stopping the system makes the process more reliable by reducing the need for physical controllers. Reducing the preparation time can save the waste of waiting time. Many methods and techniques are used to remove wastes which are the basic philosophy of lean manufacturing. Jidoka is the detection of faults in the production process and SMED is shortening of preparation times. Jidoka provides an opportunity to automatically detect the system when an abnormal situation occurs for the machine or operators and to stop the production by detecting the fault. Thus, high-quality products and productivity increase are achieved by producing faultless products, increasing quality, preventing the breakdown of machines, tools and equipments and making processes safe. Large productivity increase can be achieved by avoiding waiting wastage with the SMED. The aim of the work is to create high quality products in production and raise awareness about productivity and to make the manufacturing systems safer by shortening waiting times by stopping and detecting the faults in the production system with jidoka and SMED method as a means of lean management and lean manufacturing. In this context, SMED and Jidoka techniques were applied on called ‘’vals ball’’ in flour factory which operating in Turkey ISO top 500 industrial companies. Successful results were obtained regarding the applied jidoka and SMED techniques.

In order to survive in the global contest, enterprises have to increase their productivity via better use of their production resources. Hence, companies increasingly implementing lean management principles, which help them generate value and satisfy the requirements of their customers, through the elimination of non-value adding activities and pursuing continuous improvement in the processes.This study is an example of a process improvement that is applied to one of the fmcg company in Turkey. The project is implemented in packaging lines of Perfetti Van Melle Turkey, which is a global company, engaged in confectionery production and distribution, operating in more than 150 countries. The Turkey plant has been implementing various waste reduction practices for three years, and this project has been initiated to support the design of the packaging zone of the production system, considering the total seven wastes of lean management; namely overproduction, overprocessing, inventory, defects, transportation, motion, and waiting. It is desired to improve the performance of the packaging lines in order to keep up with the growing competition and fulfil the rapidly rising demands.The study begins by observing processes of packaging lines. The scope is determined by examining utilization rates, general line efficiency (GLE) and operational efficiency (OE). Then, selected lines are analyzed using value stream mapping (VSM) for waste identification, and statistical process control methods are implemented for improvements. The main objective is to increase the line efficiency rates that are calculated based on production quantities and scheduled time parameters. Improvement opportunities are proposed with future state VSMs by utilizing appropriate lean manufacturing techniques. Furthermore, a simulation study using ARENA Software is performed to evaluate proposed enhancements and to compare the alternative implementation scenarios.

The main philosophy of Industry 4.0 is based on intelligent systems grounded on cyber-physical systems. The more intensive use of automation in production and related functions will lead to intelligent systems and this causes less employment and changes the demographics of the workforce. Digitalization seems to have transformed our everyday lives, as well as our business and educational lives, into a technology-dependent form. Universities, which are the most important building blocks or units of social development, should take place as a driving force that must make an impact in this transformation. As a requirement of competition, the state authorities give importance to the role of the universities in this area as well as offering considerable incentives and support in the field of university entrepreneurship and they have serious expectations related to this issue. It is observed that universities have recently introduced entrepreneurial and innovative university features in their marketing activities. However, what does entrepreneurial and innovative university mean? How can an entrepreneurial and innovative university be measured and evaluated? While looking for an answer to these questions, it is necessary to evaluate the matter in the context of Entrepreneurial and Innovative University-Industry cooperation. For this purpose, based on the data obtained as a result of the interviews conducted with 19 specialist working at universities in 2017 Entrepreneurial and Innovative University Index in Turkey; and considering the impact of digital transformation and the fourth industrial revolution on social and educational processes, an industry-integrated assessment model of Entrepreneurial and Innovative Universities was developed. This model was formed within the categories of Entrepreneurship and Innovation Culture, Potential Activation, Potential Development, Projects and Commercialization and Supervision in the context of Entrepreneurial and Innovative University-Industry cooperation. As a result of the data collection, coding and analysis, the suggestions were given by defining and evaluating the 18 characteristics that the universities with entrepreneurship and innovation cultures should have in the environmental conditions, input and output dimensions.

The main reason why the concept of the internet has begun to take up more space in people’s lives in recent years is seen as computer and communication technologies that are constantly evolving and becoming widespread. The beginning of the Internet for business purposes was the beginning of the 1990’s when web browsers became available for the first time. The internet has gained importance in terms of electronic commerce activities in recent years, bringing a new trend in the form of shopping over the internet. The fact that this shopping pattern is increasingly preferred by consumers has added new dynamics to the field of business and marketing and this similar increase in internet usage began to be seen in Turkey as well as across the globe. The purpose of this study is to examine the purchasing preferences of internet consumers [1].

Due to technological developments, industrialization, rapid urbanization, and population growth the impacts of human activities on the environment are increasing all over the world. The expansion of production and consumption activities leads to more intensive use of natural resources. Hence resulting wastes, it also reached a level that threatens the environment and human health. Because of the rapidly diminishing raw material resources, and the pressure on the natural environment, the industry must adapt to more restrictive regulations enforced by governments and required by societies. As result of these environmentally conscious, Reverse Logistics has approved important attention. Reverse logistics includes the return of the products from the consumer market or the warehouse, the remanufacturing, recycling and/or the proper disposal of those products to prevent damage to the environment. E-waste sector is one of the areas where reverse logistics approach is often used in waste management. Nevertheless, there are many environmental risk factors related to the reverse logistics in the e-waste field that must be analyzed. In this study, the assessment of the “environmental risks” such as the risks of global warming due to CO₂ emissions, soil pollution risk etc. is considered as a multi criteria decision making (MCDM) problem. The Analytical Network Process (ANP) based on data collection from the experts, is used to determine the ranking of the criteria by calculating their weights. Complex Proportional Assessment (COPRAS) is applied for evaluating possible precaution strategies against environmental risks. Finally, a case study of fluorescent lamp reverse logistics process is presented to demonstrate the potential of the proposed approach. The major contribution of this work to the literature is that the environmental risk factors will be examined, prioritized and the possible precautions in reverse logistics risk factors will be discussed.

Global warming endangers our health, jeopardizes our national security, and threatens other basic human needs. Greenhouse gas (GHG) emissions mitigation is a high priority issue for most of the countries in the world. Carbon-dioxide (CO₂) is one of the most important GHG emissions, so prediction of CO₂ emissions is very important issue for the countries. On the purpose of predicting following years’ CO₂ emissions of seven developed countries; Australia, China, Italy, Spain, Turkey, United Kingdom and United States, grey forecasting method GM(1,1) which is suitable for solving uncertainty problems with less or lack of information is used in this study. Grey forecasting method is also widely used to forecast carbon emissions in the literature and generally, a few data are considered. The historical data of CO₂ emissions period between 2010 and 2014 is used to forecast the following four-year emissions, up to 2018. For the accuracy of the forecasting model, the post-ratio error (C) indicator is used which is one of the most widely used indicators for similar research. Using this model, some countries that already start to take precautions to decrease emissions could be check if they reach their target and mitigate the effects on climate change in their countries in a long term. This study can also be a counsellor or indicator for the countries that has not improved any environmental policy and chance to take into effect the precautions for their climate change plans. In other words, the methods proposed in this study can be used by countries to review their environmental policies and estimate their outcomes.

Since the quality of service is directly connected to human health in the enterprises providing services in the health sector, ensuring satisfaction by the service offered is one of the most important criteria. The complaints arise when the performance of health enterprises does not meet individuals’ health-related expectations. The strengthening of the relationship between the businesses and the recipients of the service or bringing them completely to the point of detachment through complaints is linked to the effort of health enterprises to resolve those complaints. In this research, online complaints of health care with a difficult structure to analyze, written in the natural language (unstructured) in the text form are scrutinized by the clustering method of data mining. Unprocessed (raw) data in online complaint platforms are transformed into information by processing through data and text mining methods. The results of the research are as follows: (1) to enable online complaints of health care to be divided into clusters without having to read them one by one; (2) to identify the most important elements of complaints and to divide them into categories; (3) to offer a new alternative method to health enterprises for assessing complaints vis-à-vis them.

One of the most important reasons of becoming of electronic commerce’s popular and widespread in today’s global competitive environment is to provide a new communication platform. This new communication platform is the most important feature that distinguishes traditional telephone and fax communication from interactive. This interaction has allowed many things to be done more easily in social and economic life and in particular the ability to access information quickly and cheaply. The use of the Internet and other information technologies has allowed e-commerce to evolve and expand. This study was conducted to determine the reasons why e-commerce has not been developed and the reasons for not doing e-commerce. A questionnaire was applied to 300 enterprises selected by layered sampling method operating in Kahramanmaraş. According to the survey, 118 businesses have e-commerce and 182 businesses have not. The results of the questionnaires were analyzed using SPSS 24 statistical program and the obtained findings were tested by frequency tables, cross tables and Chi-Square method. As a result, despite the fact that e-commerce firms operate, they have found that e-commerce trust, inadequate government support, lack of legal infrastructure, employees’ lack of computer and hardware and lack of internet infrastructure are seen as obstacles. The age, educational status and customer relationships subjects are ignored by companies. In this study, it was determined that age, education, and customer relations of business employees affected e-commerce. It has been determined that a majority of non-ecommerce companies’s products are not suitable for e-commerce. However, non-ecommerce companies also acknowledge the benefits of e-commerce and acknowledge that they are part of the business culture. If we focus on the above factors that hamper the development of e-commerce and strive to eliminate it, the development will be faster.

Today, when transition period to Industry 4.0 is experienced, every business has to increase productivity and reduce costs by establishing intelligent systems, to satisfy customers by increasing quality and enter a strong competition with other businesses. In this competitive environment, businesses need to constantly apply a number of improvements in order to achieve their goals, give importance to service and product improvement and to have products with low cost and high performance to operate properly. In this point, the mould manufacturing industry provides very important services in this respect. While moulds are providing high, easy and continuous production possibility, it also provides automatic production to the factory with minimum work force. In this study, the application of the Theory of Constraints was applied for solving the problems that adversely affect profitability and improving the system. In the study in which Thinking Process is applied, it was determined that the problems experienced by the operator in the process of mould delivery were experienced with “technical problems”, “quality”, “supply and purchase” and “personnel” problems. The weakest ring of the chain was searched, root problems were detected and evaporated. As a result, the improvement of the delivery period of the business has been ensured with the application of the Theory of Constraints Thinking Processes.

The paper presents the algorithm for the construction of a cutting process monitoring system for selected methods of measurement data flow in order to analyze them as a part of the Industry 4.0 idea. The effectiveness of the cutting process information flow was compared directly in the machine tool area (factory zone) and outside of it, e.g. in the office zone. A stand for monitoring of physical phenomena in the cutting zone of formation and flow of chips with the usage of a piezoelectric dynamometer, thermos-vision and quick-cage cameras was presented. The results of the analysis aimed at determining the limitations of the application of the presented measuring techniques in the concept of the idea of Industry 4.0 were presented.

Industry 4.0 is a collective term that covers many modern automation systems, data exchanges and production technologies representing the fourth revolution in the industry. This revolution allows for the collection and analysis of all the data that can affect production processes, revealing more efficient business models, and creating a structure that will completely change the production-consumption relations. When the bibliometric information of related publications are examined, it is clear that the concept of Industry 4.0 is beginning to be thoroughly debated in 2010 and later (n: 418, 81.48%), and every day of the post-publication period there is an increasing tendency. These developments affecting all areas of the industry can also be considered to affect the studies on the management of the business processes. This study aims to demonstrate how the developments in industry 4.0 are reflected in the studies related to business processes within the scope of the literature. In this context, by taking 2010 breaking point, it is investigated whether a change in the scientometric structure of the research articles related to the business processes after this year and whether the changes are compatible to the concepts conceived together with the concept of industry 4.0. As a necessary data source, the research articles that are focused on business processes in the Web of Science (WoS) database were collected, and the scientometric analyses were conducted on this data for different time intervals. For the comparisons, the similar the data on the concept of industry 4.0 were also collected and analysed. According to the search attempts on WoS on 1st of April, 2018, 6255 research articles were obtained using the phrase “business process” where 3044 of them were published in 2010 or later. Various citation mining techniques were used in the scope of scientometrics to reveal demographics and linkages. Findings show that there are significant differences before and after the year 2010.

Production related or integrated inspection of workpiece geometry is becoming increasingly relevant in modern production processes. To draw the correct conclusions for production control, the workpiece geometry has to be captured as completely as possible. Coordinate metrology with optical sensors and multisensor systems as well as coordinate metrology with X-ray computed tomography is therefore especially suited for this application. Measurement times of a few seconds can be achieved with modern technology, even with X-ray computed tomography. Thus the technology is able to follow production cycle times.

The industry sector, which is in the effort to meet market needs quickly and efficiently, has entered into the period of Industry 4.0, which means the Industrial Revolution and is called the new industrial reform, as a result of the rapid development of technology. Compared to the previous three industry periods, Industry 4.0 promises to establish a comprehensive value chain that includes all steps, including product delivery and product recycling, starting from the manufacturing intellectual milieu. This new process, which incorporates a large number of modern automation systems, data exchanges and manufacturing technologies, coupled with physical and digital technology at the same time, offers significant competitive advantages, especially if implemented correctly for developing countries. The aim of this study is to analyze the performance of IT companies operating in Turkey in the Industry 4.0 environment. For this purpose, the performances of the companies in the Borsa Istanbul IT index were analyzed by TOPSİS method and the results of the analysis and the suggestions were taken at the end of the study. R & D expenses have been determined as effective criteria for performance evaluation. BIST Informatics Index includes 6 companies whose R & D expenses are determined. The data is calculated as the ratio because of the scale size is not to affect the analysis. The data as an evaluation factor, 9 financial ratios including R & D expenses were used. As a result, in 2017, the BIST IT Index company with the highest performance was designated as LOGO.

The principal aim of this study is to determine the critical success factors of Enterprise Resources Planning Implementation and to measure their effect on Firm Performance drawing on a sample of 215 SMEs operating in Turkish textile industry. Firm performance was measured using subjective measures relying on executive’s perception of how the firm performed relative to both financial and non-financial performance criteria. The structural equation modelling technique was employed to investigate the relationship between the implementation of Enterprise Resource Planning and Firm Performance. Data analysis reveals that there is a strong positive relationship between Enterprise Resource Planning and organizational performance through Enterprise Resource Planning Performance.

Today’s more complicated engineering systems make it difficult to analyze system performance accurately due to the increase in the number of components and interconnections within the system. System performance and measures such as failure rate, repair rate and availability are important measures to analyze a system and obtain system productivity. While application of system availability is most widely used for electrical and electronic systems, in recent years it has been started to be used as a performance measure of manufacturing systems. In this study, a novel approach is proposed using both simulation modeling technique and fuzzy availability analysis considering failure and repair times of components to investigate system productivity in a more consistent and logical manner. Simulation model is also used to analyze system behavior and estimate system throughput. Because of insufficient and inaccurate historical data related with component failure and repair times of the considered system, failure and repair data are defined with the fuzzy membership function. This approach provides more detailed information about system characteristics. Thus, more realistic system productivity considering failure and repair times which represents the real behavior of system can be obtained using this approach.

Rotary elements constitute a large and significant group of machine parts. Such parts are used in various branches of industry, for example in bearing, automotive, paper, shipping or power industry. Most of rotary machine parts are cylindrical ones but sometimes other types of elements are used, as spheres, cones or barrel-shaped and saddle-shaped elements. Measurements of form deviations of such elements require performing a number of mathematical operations on measurement data, including calculation of reference features. The basis for such operations is to apply an appropriate mathematical model of the surface. Scientific literature and standards refer mainly to measurements of form errors of cylindrical shapes. Apart from the cylindrical surfaces, this paper discusses also the problem of mathematical modelling of cones, spheres and barrel-shaped elements.

Today, with the development in technology and the increase in rivalry, it is required for businesses to look for the ways to have long- lasting and ever-lasting relations with their customers based on confidence in order to obtain and keep their customers. Businesses, by preserving their present customers and learning more about them, can have long and ever lasting relationships with their customers, gain new customers through the oral advertisements of their present customers and get the edge over rivalry. At this point, relational marketing has its own place in marketing strategies as one of the top priorities in competitive conditions; it also appears as a strategy aiming at having high income as well as ensuring customer satisfaction through the quality of goods and the service and developing long-lasting and permanent relations by offered values. The most important and long term objectives of businesses replacing the service quality as the focus in marketing are to make customers prefer their businesses again and to increase the customer value by creating customer satisfaction and loyalty.In the implementation part of the study, what is studied is the effect of the service quality as a component of relational marketing strategies being implemented by jewelers; and the satisfaction and the loyalty within the offered values of customers who have bought gold/jewelery from the jewelry stores in Konya.As it is vital for businesses during implementation to know about the effects of the service quality and relational marketing implementations accepting the offered values factors as a key component in creating customer satisfaction and loyalty, it will be an advantage for them to see their investments made to the relationships not as an owning cost but as an executive strategy that will enable a value of return.

The world of standardized management systems is traversing exciting changes with the publishing of the long-awaited ISO standard for occupational health and safety, ISO 45001. It comes to join ISO 9001 and ISO 14001 to form a trio of highly compatible best practice references of interest for many companies that want to become more competitive, especially from the manufacturing sector. For the past at least 20 years there have been many debates and studies on how to best go about using these standards together to set up an integrated management system. Of course, things seem easier now, but together with the benefits, there are also challenges to manage and some are quite significant. This paper discusses the implications of reaching this milestone and presents the results of a focus-group made among production oriented companies, that was aimed at probing the stakeholder community regarding its positioning in the new context. The focus is on the impact of the new regulations upon creating or upgrading an integrated management system, where relationships among components are the key to a successful implementation and to obtaining results.There are three main parts to the paper, a literature survey meant to catch a glimpse of the changes taking place within the complexity and depth of the topics approached in the field, a theoretical analysis of the main implications of the changes performed within the standards line-up and a qualitative interview asking questions about the benefits and challenges identified by the companies going through the process of upgrading their integrated management systems in the new context.

The mining sector is one of the most important raw material sources and wealth sources for countries. On the other hand, many work accidents occur during its activities due to the adverse working conditions. Research is being conducted to reduce the security risk factor, which is one of the most critical obstacles to the social sustainability of the mining industry. In this study, under-recorded mine accidents and injuries are handled, rather than the accidents of the roof falling and the explosions which are frequently considered in the literature. In this scope of the study, accidents and incidents that occur during the specified processes (support, face, loading and transportation activities) of an underground chrome mine are investigated. Expert judgments have been used since no past accidents are allowing statistical inferences. BN has been used to find out the issues about the safety risk by addressing the causal relationships between the events. OHS education, OHS inspection, employee attention and, rock and ground structure of the working area have been deduced as the root causes of the accidents which occur mostly during the labor-intensive processes. By using the updating ability of the BN, comprehensive sensitivity analysis has been performed with the new information related to root causes. According to different scenarios associated with the various states of the root causes, the results and the future suggestions are presented.

The elderly population in the world and Turkey is increasing rapidly. The proportion of elderly people in Turkey that has remained below 5% until the 1990s has reached its highest point in the past 15 years with a significant increase. This leads to an increase in the need for nursing homes. However, for those living in nursing homes, spatial risks can lead to serious hazards such as injury and death. To increase the quality of life for the elderly, these hazards should be assessed, and corrective actions should be taken to eliminate them. The Fine-Kinney risk analysis method is one of the most commonly used methods for risk assessment. In this method, the hazards are evaluated according to the probability, frequency and severity factors. However, the value assignments of these risk factors are often based on expert opinion. Experts often identify risk values in the context of incomplete information and uncertainty. Also, experts tend to use verbal expressions rather than numeric value assignments. In this study, a fuzzy Fine-Kinney risk analysis approach was developed to take advantage of fuzzy logic to remove this shortcoming. This developed approach was applied to the nursing homes located in Istanbul and the areas that need to be improved with high risk were determined first. The order of risk prioritization obtained with the fuzzy Fine-Kinney approach was compared with that of the conventional Fine-Kinney method and it was determined that the fuzzy Fine-Kinney approach gave better results.

This document presents the idea of the machining process optimization in the concept of Industry 4.0. The authors proposed the method which mainly is designed to optimize the machining process of parts made of hard-to-cut materials with complex geometry. The optimization research allowed to gradually increase the efficiency of the machining while ensuring the required surface roughness. The optimization procedure caused also a partial stabilization and reduction of the maximum values of the cutting forces.

Our focus in this study is the vehicle dispatching, routing and packing problem of a cargo company branch in Izmir, Turkey. The daily problem involves determining which parcels or packages should be distributed in which vehicle, determining the order in which these packages will be deployed, determining the route through which the vehicles will make the distribution, and finally determining how the packages should be placed in the vehicles. Thus, the whole daily distribution process of the cargo branch is of focus. We develop a web-based decision support tool to handle this hard-to-tackle problem. Within the decision support system (DSS), we handle the problem in stages. By developing an intuitive algorithm, the delivery route-based three-dimensional packing is solved very quickly. The results are shared with the user through a user-friendly interface.

The main purpose of the study is to design a forecasting framework through a better understanding of the structure of the customers’ own forecasts to minimize the forecast error. Different than the conventional forecasting methods, our framework has an extra input, which is the set of reported customer forecasts; which is mostly based on customers’ own production plans and capacities. Furthermore, our framework also takes the advantage of the classical methods: Winter’s Method in its pure form and Winter’s Method merged with Decomposition Method are taken into consideration, because these methods are able to handle stability, seasonality and trend in the demand data structures. The general proposed model is designed to embed the customer forecasts to the forecasting framework with a scientific methodology. A new method is created with a logic of a calculation of reliability indices for each customer and product pairs with following some statistical procedures. As a result of the method which can calculate the reliability of each customer, a forecast output is provided. On the other hand, forecast Combination Method is adjusted with respect to the nature of the problem to combine the output of Winter’s Method’s and the output of Customer Forecasts Method. In order to implement all these methods, the study is practiced in a well-known, international energy company. The demand data are divided into such subgroups as; Regular, High Variance, New Born, Rare, On Off and Inactive based on the demand structure of the data, to observe how these subgroups would react to the method. In order to achieve all these routines of the forecasting framework, we design a Decision Support System in Excel Visual Basic Applications (VBA).

This study involves in a real world application of permutation flowshop scheduling problem (PFSP) in a local company that produces apparel and garments. Various test jobs arrive in the quality control department and a schedule has to be prepared considering the test stations and processing times. A job consists of a series of operations on certain stations. Each station is designed to perform a particular test operation. Therefore, there are jobs waiting to go through a series of quality control operations on various stations. Each job has different processing times at stations. Moreover, different jobs may have different processing times at a particular test station. However, the operation sequences (routes) of all jobs are the same through the stations. It is not allowed to change the order of the jobs on different stations. This problem falls into the realm of permutation flow shop scheduling problem (PFSP) in the literature. Various mathematical models are defined in literature for the optimal solution of the problem. One of them was chosen and used to solve small-sized problems. However, as the size of the problem increases, and since the problem is shown to be NP-hard for three or more machines, the solution time increases rapidly and hence it becomes significantly hard to solve the problem in polynomial time. Therefore, a combination of two heuristic methods is employed to solve the problem in reasonable time. First, NEH (Nawaz, Enscore, Ham) method is used to obtain a good initial feasible or a near optimal solution and then iterated local search method (ILS) is engaged to improve the solution. This solution procedure is implemented in a decision support tool in order to develop efficient schedules for quality control jobs in the company. The performance of the procedure is evaluated and verified by comparing the solutions with the optimal solutions of small sized problems. The tool can also be used for educational purposes since it is user friendly and has ability to present outcomes in detail with proper graphics.

This study is about real-life production and capacity planning problem in an international company which operates in energy management sector in Manisa, Turkey. The company produces different types of circuit breakers and delivers its products to different countries and distribution center, located in France. Within the scope of this problem, the production plan is done for nine products that are manufactured on six production lines. Each product has a unique production line, but some of the products are processed on common production lines. In this study, the production lot amount is determined each day by considering the due date and quantity of the customer orders without exceeding the capacity of the production lines. In the existing system, there are many tardy and early customer orders and the production plan is done manually which causes time loss for the company. A preemptive goal programming model is proposed for solving this problem where the main goal is to minimize total lateness in customer orders and minimizing the number of customer orders that have been split is considered as the secondary objective. The proposed mathematical model is solved optimally for real life instances in IBM ILOG CPLEX Optimization Studio 12.6.3. In addition, a heuristic method is presented in order to decrease the daily production planning duration and the fulfill the company’s needs. Moreover, a user-friendly decision support system is developed where both solution techniques are embedded.

This paper conducts our senior project at Altın Yunus Hotel located in Çeşme, Turkey and it contributes to the improvement of operations management of the hotel, focusing on the front office, reception and housekeeping services. The problem is determined as the housekeeping problem in consideration of other problems described in detail in the following sections. Required data are provided by the hotel management. The aim of the study is to develop a decision support system (DSS) covering and increasing the efficiency in service quality. Through the literature survey, system analysis and the developed mathematical models such as regression, time study, worker assignment, uniform parallel machine scheduling and routing optimization are presented. Finally, achieved time and cost savings are presented.

Increased competitiveness leads the importance of efficiency analysis for organizations. There are many tools and techniques for performance measurement. Data Envelopment Analysis is one of the well-known nonparametric, direct programming technique that can deal with multiple inputs and outputs and used for efficiency analysis. In this study, data envelopment analysis is used in retail sector. This study is based on a real life problem and the aim is to measure the store performance of a local retail chain in Turkey. While, size of the store, number of employees, number of deliveries and total cost are used as inputs; number of customers, sales, and store evaluation of customers are used as outputs in this study. Main contribution of this study is using store evaluation of customers as an output by conducting an interview with each stores’ customers. Due to the dynamic environment of the retail sector, model that allows variable return to scale while maximizing inputs; input-oriented BCC is used in the study. At the end of the study, numerical results are obtained from a software called Frontier Analyst, and managerial suggestions are presented in the conclusion part.

Changeover time is a time between last good product of a specific model, to a first good product of another specific model. During this changeover time, materials, equipment and layout can be changed and this causes non-value added activities. This study aims the reduction of changeover time losses in the sixth line of a worldwide factory which produces combi boilers. Before developing the solution alternatives, causes of time losses were determined. After that, solutions have been searched with process design improvements. A simulation model and decision support system were generated to set the differences between proposed and current situation. While developing solutions, for specific symptoms, various technics were used such as 5S, Lean Manufacturing methods and Quality Function Deployment. Based on these studies, the current situation of the assembly line during changeover process has been improved.

With the increase of global trade activities and the decrease in transportation costs, the volume of international trade has grown considerably, yielding to an increase in the logistics activities as well as the number of containers used in transport. Hence, containers gradually deteriorate over time and logistics companies start to diminish the repair costs of the containers, as well. This study addresses the repair cost minimization problem for containers where the objective is to minimize the total transportation, repairing and delay time costs. The problem is formulated as a variant of the well-known transportation problem, where we assume that the broken containers transport to repair depots, and the fixed containers are delivered from the repair depots to the customers until the requested due date. In order to monitor the performance of the proposed model, realistic test instances are constructed. Optimal solutions are achieved within 40 min for relatively small and moderate test instances.

An optimal container dispatch planning model for Alkon Logistics is proposed. Alkon Logistics handles container movement between three large ports and a logistics center nearby, connected to major highways and railroad systems. As a solution approach, a novel integer mathematical model has been developed to minimize total cost of operations. Our model is developed to serve three different ports, which are T.C Ege Gübre, Nemport, and APM Terminal. In addition to making daily operational decisions optimally, the proposed model also assists in making critical long-term decisions, such as vehicle investments. Our model is applicable to any transport company, which carries single-commodity due to its flexible structure. Proposed model is solved using IBM ILOG CPLEX Optimization Studio 12.8 program and tested with real-life data from the company. The results show significant improvement over the current situation. To ensure efficient usage of the proposed approach, a decision support system (DSS) is designed and implemented that allows studying different scenarios. Created DSS is dynamic and practical for users and enables making analysis by using mathematical model with different fleet sizes. Results from experimentation show that compared to current situation, number of rented trucks goes down to less than 10 from 17 corresponding to a decrease in renting cost by 65% and a decrease of 25% in total cost. Proposed solution methodology provides a container dispatch planning with improved truck utilization and optimal cost.

The pallet loading problem considers the loading of rectangular-shaped boxes with known dimensions into the pallets. In this paper, a real-life pallet loading problem of a beverage company is studied. In this problem, the aim is to maximize the total loaded box volume on pallets by employing a three-dimensional approach, where overlapping of any two boxes is not allowed and the fragility relationship is regarded. As a solution approach, a heuristic algorithm and a mathematical model have been proposed and verified with a computational experiment. A sensitivity analysis is also performed for the parameters of the problem. Furthermore, a user friendly decision support system, which is integrated with IBM ILOG CPLEX, is developed using Excel VBA interface. The proposed solution approach is embedded in this decision support system. It is estimated that proposed solution method will prevent the field loss due to the improper loading and reduce the financial damage, as it reduces the dependency on operators and the decision-making duration. As this problem can be seen in various companies, the proposed solution approach can also be employed by different sectors and companies.

This study involves in a real-world application of 3-D cutting stock problem in a local bedding company. The company produces various types of mattresses (beds). The bill of materials of a mattress usually includes foam rubber (sponge) components. Each mattress has different foam rubber components in the form of orthogonal rectangular prisms with different dimensions. Those components should be cut from big foam rubber blocks. The properties of current cutting machinery used in the company imposes “guillotine” cuts. The aim is to minimize total waste in cutting operations. There are mathematical models to solve cutting stock problems, however they require “cutting patterns” to be generated in advance. Cutting patterns represent potential combinations of how rectangular prisms are fitted into foam rubber blocks. Column Generation method and a Branch and Bound algorithm are used to generate cutting patterns. Mathematical model then solves the problem provided that the cutting patterns are supplied as input. A user friendly Decision Support System (DSS) has been developed in order to incorporate proposed procedures to solve the problem. It enables the user in the company to prepare efficient cutting plans easily and quickly.