Advances in Production Management Systems. Production Management for Data-Driven, Intelligent, Collaborative, and Sustainable Manufacturing

Table of Contents

1. Frontmatter

2. Lean and Green Manufacturing

   1. Frontmatter

   2. Reverse Logistics Route Selection Using AHP: A Case Study of Electronics Scrap from Pakistan

      Fahad Mushtaq, Muhammad Shafiq, Matteo Mario Savino, Touqeer Khalid, Marialuisa Menanno, Ali Fahad

      Abstract

      Selection of optimal route among available choices in the presence of various factors has been a prime focus in logistics. In this paper, Analytical Hierarchy Process (AHP) is used for selection of optimum route among available options for revere logistics of electronics scrap from Pakistan to the industry using End of Life (EOL) products as there raw material. The main objective of this study is to find out the optimal reverse logistic path for electronic scrap considering: cost of transportation, time of transportation, volume of goods to be transported, nature of goods (refurbished, recyclable or scrap), and financial value of the goods being transported. Recently developed China Pakistan Economic Corridor named as CPEC is also considered among available routes which are being analyzed. The results show that CPEC is the best possible route. In addition, the proposed mechanism also provides hierarchical list for the possible route preferences which helps in finding an alternate in case the best/better route isn’t available due to some unavoidable factors.

   3. Digital Lean Cyber-Physical Production Systems: The Emergence of Digital Lean Manufacturing and the Significance of Digital Waste

      David Romero, Paolo Gaiardelli, Daryl Powell, Thorsten Wuest, Matthias Thürer

      Abstract

      This paper explores the emergence of the next cyber/digital frontier for lean manufacturing practices. It focuses on (a) the new capabilities of information and operational technologies (ITs/OTs) for proactively detecting and eliminating potential ‘physical waste’ in production processes, preventing its manifestation in the real world through powerful virtual models and simulations as well as real-time performance monitoring systems based on advanced data analytics, and (b) on identifying and eliminating ‘digital waste’ that may come into existence in the cyber world due to the non-use (e.g. lost digital opportunities) and/or over-use (e.g. abused digital capabilities) of new digital/smart manufacturing technologies.

   4. Effect of Prioritization on the Waiting Time

      Yannic Jäger, Christoph Roser

      Abstract

      In industry, it is common to prioritize some orders over others. This is done to reduce the lead time and waiting time of these prioritized orders, hence the customer will get the order earlier than otherwise. However, whenever an order is prioritized, the remaining orders are de-prioritized, and their lead time and waiting time will increase. In industry, a rule of the thumb that no more than 30% of the orders should be prioritized is often used. This paper will verify this assumption using simulations for different conditions. It will show that this rule of thumb is generally a valid approach. The paper will offer more detail on the trade-off between prioritizing some orders and hence delaying other orders.

   5. A Small Dice Game for the Kingman Formula

      Christoph Roser, Masaru Nakano

      Abstract

      There are three main factors influencing the waiting time of a single-arrival single-process system: the utilization, the fluctuation of the arrival, and the fluctuation of the process time. The influence of these is not linear, and the combination of these effects is worse than the individual sums. Different approximations exist for this relation, the most popular one being probably the Kingman equation. Now it is one thing to understand this in theory, but experiencing this in practice makes it much easier to understand and will prepare practitioners much better for its effect. This paper describes a quick and easy game to have the practitioners experience the individual and combined effects of both utilization and fluctuation.

   6. Towards a Sustainable Innovation Process: Integrating Lean and Sustainability Principles

      Myrna Flores, Doroteja Maklin, Billy Ingram, Matic Golob, Christopher Tucci, Andrea Hoffmeier

      Abstract

      Many companies are heavily investing resources to innovate faster and smarter in order to gain or retain a competitive advantage. Nevertheless, defining and deploying a sustainable innovation vision still represents a challenge to most companies, as a deep change of mindset is required to reflect going beyond the design, development, production and distribution of new products, to also consider their disposal, recycling or reuse, as part of their end-to-end product life cycle. Therefore, this paper aims to: (1) highlight the relevance of including lean and sustainability principles in the early design and conceptualization phases, (2) explain how lean and sustainability can bring benefits when applied as an integrated system considering three axes: the economic, the social and the environmental, and (3) share a case study providing insights of a successful application.

   7. Mathematical Modelling for Sustainable Agricultural Supply Chain Management Considering Preferences Between Farmers and Retailers

      Takashi Hasuike, Tomoko Kashima, Shimpei Matsumoto

      Abstract

      This paper considers an agricultural supply chain management to find the best matching between farmers and retailers with contract according to their preferences. It is important to construct the agricultural production system to hold the win-win relationship considering transportation costs. Therefore, in this paper, a mathematical programming problem is formulated to find the optimal matching between farmers and retailers under several uncertainties. It is generally difficult to obtain the best solution directly in terms of multiobjectivity and uncertainty. Therefore, the flexible modeling and the efficient algorithm to obtain these optimal solutions are also developed using a data-driven approach using our proposed information system.

   8. Formalising Specific-Energy Consumption Under a Production-Management Form Where Rush Orders Are Added in Time Slots

      Shungo Arai, Hironori Hibino, Takamasa Horikawa, Makoto Yamaguchi

      Abstract

      Factory-production activity is conducted based on production plans, which will unavoidably have to be revised due to changes in the production context. These changes should be considered when drafting production plans because of the frequent occurrence of rush orders with short deadlines. Since rush orders interrupt regular orders, we may consider that increased setup times, lower production quantities, and increased specific-energy consumption will accompany their addition.

      We have previously supposed a management form that immediately adds rush orders to the production line, and proposed expressions for calculating the specific-energy consumption. Actual companies, looking to restrict increases in setup times, may implement management where rush orders are accumulated and added in time slots. However, in studies on formulae for calculating specific-energy consumption that consider rush orders, we see no consideration of management where the rush orders are added in time slots. Accordingly, this study presents a pre-emptive evaluation method using specific-energy consumption by formalising it for management where rush orders are added in time slots.

   9. Implementation Challenges Affecting the Environmental Improvement Performance in Pharmaceutical Production:

      Results of a Green Kaizen Pilot Seyoum Eshetu Birkie, Martin Kurdve, Monica Bellgran, Jouni Korhonen

      Abstract

      This paper reports on working findings in an action research-based project, implementing a green kaizen pilot in a European pharmaceutical manufacturing company. The aim of the study is to investigate how continuous improvement initiatives with focus on environment originally developed for the automotive manufacturing industry could apply to the pharmaceutical industry. It also aspires to understand the enabling and hindering issues are for such implementation. There are considerable similarities of implementing lean in general in the two sectors, however, some key differences and challenges were apparent when implementing this specific green kaizen method called Green Performance Map. An implication for pharma practitioners implementing the green kaizen method concerns how to improve working procedures and production equipment to become more environmentally friendly amid high regulatory demands on process quality. Implementation challenges are discussed in terms of fidelity, locus and extensiveness of lean practices implementation.

   10. A Stochastic Programming Model for Multi-commodity Redistribution Planning in Disaster Response

       Xuehong Gao, Gyu M. Lee

       Abstract

       When a large-scale disaster occurs, a set of relief centers should be determined to accommodate evacuees and a variety of multi-commodity should be distributed to these relief centers to provide basic life support. Because the multi-commodity distribution at peacetime may be imperfect and unbalanced, the surplus commodities in some relief centers can be redistributed to other relief centers with shortages, to make the effective and efficient use of these commodities. This multi-commodity redistribution problem is also an important issue in the emergency management. Various uncertain elements include transportation network, supply and demand, making this problem a big challenge. To handle this problem, a two-stage mixed-integer stochastic programming model was proposed to facilitate this multi-commodity redistribution process. In our model, we define the dissatisfaction cost based on the relief center size, unmet demand and oversupply of commodity in the relief center. Then, our objectives are to minimize the total dissatisfaction cost in the first stage and minimize the total transportation time in the second stage, sequentially. Finally, a randomly generated numerical instance is tested and computational results show that the proposed model can provide effective and efficient decisions in the multi-commodity redistribution process.

3. Operations Management in Engineer-to-Order Manufacturing

   1. Frontmatter

   2. Dual Resource Constrained (DRC) Shops: Literature Review and Analysis

      Matthias Thürer

      Abstract

      The majority of manufacturing systems in practice are constrained by machine capacity and labour capacity. Consequently a broad literature on Dual Resource Constrained (DRC) shops exists. However, to best of our knowledge, no systematic review of the literature has been presented. Rather, existing reviews follow an ad-hoc procedure for article selection. In response, this study presents a systematic review of the literature concerned with DRC operating issues, such as worker assignment and production planning and control methods. Results highlight that, while early literature on dual resource constraint job shops was mainly simulation based, recent literature tends towards advanced scheduling mechanisms. This arguably introduces a bias towards deterministic contexts. Moreover, most DRC literature focuses on shop floor control decisions as labour assignment and dispatching. This neglects higher-level planning and control methods, such as order release control.

   3. Controlling Customer Orders in the ETO/VUCA Contexts

      Stanisław Strzelczak, Viswavikram Viswanathan

      Abstract

      Under hyper-competition customers expect to accept last-minute changes in their orders. In such circumstances ETO manufacturing exhibits the VUCA specificity and suffers from many issues like delays, excessive costs, low quality etc. This paper examines operative controlling as a mean to facilitate discovery and response to the changes and disturbances. The approach derives from the phenomenological research and the reflection on theory and practice. The solution uses an integrated model that represents all workflows subject to changeable contexts and is based on three pillars: (i) run-time data extraction; (ii) integrated representation of workflows; (iii) providing current information to shareholders. The concept was validated by prototyping and a use-case.

   4. Defining Solution Spaces for Customizations

      Nikolas Käkelä, Joakim Wikner

      Abstract

      Customization in different flavors have been identified as an important differentiator if low-cost competitiveness is not viable. To provide a customer unique solution is however not the same as providing a solution that is designed and individualized for a particular delivery to a customer. These two cases are illustrations of how customer requirements may be fulfilled differently depending on the match between stated requirements and the solution offered. The range of solutions that can be offered is represented by a solution space consisting of either predefined or postdefined solutions. Predefined refers to solutions that are defined before commitment to a customer and postdefined refers to solutions that are defined after commitment to a customer. Both cases are constrained by a boundary of possible solutions but the postdefined solutions provide opportunities for bounded innovation beyond what the predefined solutions can provide. Combining the properties of the different solution spaces provides not only an operational definition of customization but also supports in identifying strategic opportunities for extending the solutions and types of customizations a business provides.

   5. A Conceptual Framework for Stage Configuration

      Bjørn Christensen, Thomas D. Brunoe, Kjeld Nielsen

      Abstract

      Increased competition for creating best business cases in the ETO and capital goods industry forces companies to provide increased variety of product configurations to match diverse operating conditions, while simultaneously reducing the cost of supply. The ETO and capital goods industry is further characterized by rapid new technology introductions, constantly setting new standards in product performance and by an external environment with frequently shifting local regulations. To remain competitive in this volatile and unpredictable situation, this paper suggests a conceptual framework enabling companies to align new product development with sales order processes in a step-wise approach using product configuration. This alignment supports a five-stage approach in committing order specifications, thereby postponing configuration decisions according to the maturity of the sales order. Moreover, the stage-wise postponement enables the management of product specifications on different aggregation levels. The committed level of specifications, targets the relevant decision-making processes in product configuration without needless over-specification of the product. The stages are (1) qualifying a sales opportunity, (2) recommending an optimal solution, (3) signing the sales offer and performing supply chain planning, (4) releasing the order for production and completing customer specific design, (5) executing production, transportation and service operations.

   6. Dynamic Weight Configuration of Dispatching Rule Using Machine Learning

      Jong-Ho Shin, Chaekyo Lee, Sangrae Kim, Jun-Gyu Kang

      Abstract

      The manufacturing execution systems (MES) is one of the key elements consisting smart factory. It is responsible for shop floor control by performing managing resources, dispatching production orders, executing production orders, collecting production data, analyzing production performances, and so on. Through these functionalities, the MES aims high productivity. The dispatching in the MES helps these aims. The selection of job in manufacturing execution systems (MES) is performed by dispatching rule. The dispatching rule is composed of several factors affecting scheduling objective and constraint. In most cases, the dispatching rule is expressed as the weighted sum of factors and the weight moderates the relative importance among factors. To find optimal weight configuration requires heavy calculation burden so that it cannot adapt dynamic order changes. To solve this problem, one of machine learning algorithms is used in this study. The multi-layer perceptron learns the best weight configuration according to orders and predict the best weight configuration for new orders. The proposed method is tested by field data and proved its usefulness.

   7. Customizations vs. Platforms – A Conceptual Approach to COSI

      Jenny Bäckstrand, Martin Lennartsson

      Abstract

      In recent years, many manufacturers have experienced an increased demand for customized products and services, which requires the manufacturer to simultaneously offer both standardized and customized products. Consequently, several manufacturing strategies must be efficiently employed. These companies do not express the same prerequisites as ‘pure’ ETO companies since they need to be able to differentiate customized orders from standard orders, but also be able to differentiate between the manufacturing dimension and the engineering dimension of customization. Whereas standard orders can be processed with a platform approach, the customized orders contain specific requirements and information represented by ‘customer-order specific information’ (COSI). This paper defines and presents competitive scenarios where platform constraints are combined with COSI for efficient customizations. Implications for the approach and a path forward is discussed.

   8. Barriers and Success Factors for Continuous Improvement Efforts in Complex ETO Firms

      Emrah Arica, Kristoffer Magerøy, Marta Therese Mathisen Lall

      Abstract

      This paper focuses on the factors that may influence the implementation of continuous improvement efforts, in an Engineer-to-Order (ETO) manufacturing setting. In general, one-of-a-kind production nature and temporary organizational structures of ETO firms may hinder the successful implementation of continuous improvement programmes. This study investigates this issue deeper through a single case study in a producer of offshore oil platforms and outlines the barriers and success factors for continuous improvement in ETO manufacturing.

   9. Engineering Change Management in the Engineer-to-Order Production Environment: Insights from Two Case Studies

      Natalia Iakymenko, Anita Romsdal, Marco Semini, Jan Ola Strandhagen

      Abstract

      Engineering changes (ECs) are part of any Engineer-to-order (ETO) project. The engineering change management (ECM) literature provides various tools, methods and best practices, and this study investigates ECM practices in the ETO production environment. Through two exploratory case studies, we identify five main ECM challenges; EC impact analysis, EC data management, internal and external collaboration and communication, and EC post-implementation review. Both companies have implemented the main ECM steps recommended in literature but there are considerable weaknesses in the execution of the post-implementation review process. More ETO cases are needed to confirm the findings and investigate how ECM tools and approaches vary by different dimensions.