Product Lifecycle Management for Digital Transformation of Industries

Knowledge is a major source of competitive advantage. Hence, industry has developed tools to capture and reuse its knowledge in the development of new projects and products. Information practices and learning strategies, as Knowledge Management, are gaining acceptance also in the field of education. However, the use of these tools are limited to staff applications and they are not being employed in the university core business: education. This paper shows how a tool to build and validate internal combustion engines, developed in industry, has been successfully integrated into a university course. The learning process has being greatly enriched by the use of this application. Evidence on the planned improvements are also presented.

The research work reported here is part of a larger project aimed at acquiring knowledge about issues in assembly, from documents. In order to do so, the first step is to identify the presence of issues. For this, sentiment analysis is proposed as a means. The presence of issues is proposed to be found by detecting negative sentiment. However, general English sentiment lexicons are not enough to detect negative sentiment in specialized domains, in this case, aircraft assembly. This paper studies an existing sentiment analysis tool, and creates an enhanced sentiment lexicon on the basis of the performance of the tool. The enhanced domain lexicon is proposed as the solution to identifying domain specific issues.

Whenever a new technology is made available, it is worth finding possible uses in different domains. The advancement of information technologies now enables a wealth of information to be digitally collected and exploited for knowledge management and reused for further knowledge creation. Big data enables organizations to capitalize on large amounts of data by bringing together different sources of information to find trends and knowledge that are only visible with large amounts of data. This knowledge can then be applied for knowledge exploration, exploitation and decision making.

This article presents an integration of a product design methodology with emphasis in ergonomics with PLM. The articulation requires a comparative overview of the management levels offered by both approaches. PLM focuses on procedural activities and task performance and supports the ergonomic design methodology into a project and process management level in which decisions and control claims a mayor role. As result, workflow and indicators solutions attached to PLM strategy approach are structured accordingly to particular needs of the methodology in question.

The re-use of product knowledge is vital to the development of Knowledge-Based Engineering (KBE) systems and to the deployment of Product Lifecycle Management (PLM) strategies. This paper addresses the challenges related to KBE-PLM systems integration in order to unlock engineering knowledge from proprietary representations and to manage the lifecycle of KBE models as well as their usage by different design automation applications. Essential constituents of product knowledge are identified and analyzed and the concepts of design intent and design rationale are re-introduced as key enablers to re-use this product knowledge in the appropriate KBE context. The paper introduces a KBE-PLM integration framework including a platform-independent Open KBE repository structured according to the KBE-PLM integration schema. This schema is a multi-layer neutral product and knowledge data model designed for integrating information from parameterized Computer-Aided Design (CAD) models, rule-based KBE systems and PLM systems.

Research on process mining and machine learning techniques has recently received a significant amount of attention by product development and management communities. Indeed, these techniques allow both an automatic process and activity discovery and thus are high added value services that help reusing knowledge to support decision-making. This paper proposes a double layer framework aiming to identify the most significant process patterns to be executed depending on the design context. Simultaneously, it proposes the most significant parameters for each activity of the considered process pattern. The framework is applied on a specific design example and is partially implemented.

This paper aims at closing the gap between early phases (e.g. design) and later phases (e.g. procurement or production) of the Product Development Process (PDP) by proposing a Virtual Product Model (VPM) as a collection of individual components (VPMCs) without the need for a static structure. Based on an analysis of the requirements on product development in the automotive industry, the main problems we observe are limited transparency, limited continuity, and limited reusability throughout different phases of the PDP. Virtual Product Model Components (VPMCs) can be used in different products and allow the reflection of changes throughout the PDP as well as the derivation of domain-specific views on the overall product at runtime. We illustrate these concepts by use case scenarios derived from an analysis of automotive product development practices.

In mechatronic design processes the exchange of information between stakeholders from different disciplines is essential to enable simultaneous engineering and a successful integration of domain specific subsystems. Although there is a comprehensive range of methodologies and tools to support collaboration, intentions to implement a central data management platform covering all stakeholders often do not succeed. Reasons are the heterogeneous model landscape, the variety of stand-alone authoring tools, departments’, disciplines’ or companies’ boundaries and a lack of flexibility of established solutions regarding the support of unpredictable and quickly changing design processes. This paper focuses on the management of individual parameters and parameter instances (values) within a multi-disciplinary development team. The presented lightweight approach can extend existing methods and data management infrastructure by adding functionalities to provide access to individual parameters using a dedicated database. The procedure is shown by the example of a technical mechanism.

Interface in one complex system represents the logical or physical relationship integrating the components of the complex system or the components with their environment. It plays a quite significant role to guarantee the components designed by the designers of different disciplines integrate correctly in order to achieve the multidisciplinary integration. This paper presents an interface knowledge base to capitalise the design data and rules related to the interfaces. A knowledge-based engineering (KBE) design methodology in which the interface knowledge base is implemented is then proposed to help the designers to improve the multidisciplinary integration during the detailed design phase of complex systems. This KBE design methodology is finally demonstrated by a case study based on a partial discharge (PD) detection system.

The enterprise collaboration has gain much popularity and strength with the inception of digital revolution. The concept of enterprise collaboration has observed a dynamic and evolving phenomenon of value added chain. This phenomenon under the convergence of information technology has placed a remarkable impact on decision-making processes within enterprises. The enterprises are involved in establishing a common window of collaborative network where the principle enterprise decides the synthesis of the incoming opportunity. In this study, we have shown how the decision-making capability can be improved by means of analytics of vast amount of data during enterprise collaboration. The proposed system has adopted prescriptive analysis across enterprise resources. The outcome of proposed system addresses the individual and collaborative enterprise capability within enterprise network. Our proposed knowledge based decision making model provides a self-adaptive solution for enterprise collaborative services.

This paper presents a method introducing Agile practices in project planned methodology in the context of a multidisciplinary product design. These multidisciplinary products can be Mechatronics or Cyber-Physical-Systems. Various design methodologies and types of project architecture already exist. Some of them are focused on a micro-level, whereas others are on a macro-level. Our proposition is focused on the macro-level. Agile and project-planned methods are presented and analyzed before looking at a possible hybridization. Hybrid solutions already exist, but this paper formalizes a project architecture to combine the advantages of project-planned and Agile methods and to describe the relative PLM position.

Smart manufacturing requires digital product data to be shared and exchanged among numerous engineering applications and information systems. But no single product data standard can satisfy every integration scenario. Customizable standardization frameworks for Product Lifecycle Management (PLM) attempt to address this problem by allowing users to add new information structures to an existing data model in a controlled manner. A PLM information model may be either flat or hierarchical. We discuss two approaches. One is based on ISO 10303-239 as an exemplar for customizing flat models. The other is based on Open Application Group Integration Specification (OAGIS) as an exemplar for customizing hierarchical models. We evaluate the two approaches and observe that the type of model strongly influences how well the PLM standardization framework meets each evaluation criterion, and that the best choice is use-case dependent.

This paper proposes a model-driven interoperability framework as a technical support of co-evolution strategy of product structure and production systems with a frugal innovation perspective. Based on the modularity concept, the role of this framework is to connect possible product modules managed in the Product Life cycle Management tool to all possible production capabilities managed on the Manufacturing Process Management tool, and able to realize each module. This will help designers to define the optimal product architecture based on technical features of modules regarding the functional requirements as well as the optimal production strategy.

To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformation rules based on the domain knowledge of manufacturing engineers and data scientists. Our approach uses a model of a manufacturing process and its associated data as inputs, and generates a trained neural network model as an output to predict a quantity of interest. This paper presents the domain-specific knowledge that the approach should employ, the formal workflow of the approach, and a milling process use case to illustrate the proposed approach. We also discuss potential extensions of the approach.

The semantic interoperability of information has become increasingly important in Product Development Process (PDP) to support different phases during the product development. This article presents a proposal of an Interoperable Product Design and Manufacturing System (IPDMS) concept based on a set of engineering domain ontologies and sematic mapping approaches. The concept explores the potentials of semantic well-defined core-foundations in a Semantic Web ontology language. The formal core-foundations can be specialised to perform application view in Product or Manufacturing Model. The application view is used to support the information sharing between product design and manufacturing and verify the accordance with product requirements. A preliminary experimental has been realised, using a test case to share information from the design to manufacturing of an injection moulding plastic. As results, it was identified potential benefits and limitations. The mains contributions are: semantic interoperability during information sharing in PDP and analysis of inconsistencies in PDP.

Metallurgical equipment belongs to the discrete manufacturing industry, in which large-scale equipment is common, and has feature of high level of customization, large variety, single and small batch. Under the model of design to order, R&D staff have to modify or redesign according to each order, leading to longer product development cycle and higher cost. This paper presents w-model of system engineering framework to solve the R&D cross sectoral collaborative problem. Top-down functional decomposition integrated with bottom-up component clustering is suggested by the author to form module for design knowledge reuse. In the end, this paper takes an illustrative example of lean metallurgical equipment development to demonstrate the feasibility and technical advantage of the approach.

Lean Product Development (LPD) promises high product development success by strongly relying on knowledge. Though, despite many IT-based knowledge management tools exist to support and enable knowledge capture, use, formalization and reuse in product development, such as Product Lifecycle Management (PLM) systems, their use within the LPD context is either low or not discussed. This research aims at starting a debate on the role such technologies could have in LPD applications and product development success. The study involves two independent empirical research initiatives, one in France and one in Italy, and launches a discussion on the role of PLM in customer value definition in LPD initiatives.

First developed for manufacturing context of the Toyota Production System, the Lean approach has been extended to product development about 20 years ago. Lean Product Development approach emphasizes on a method to implement a flowing development process. However, some tasks require decision milestones that can interrupt this continuous process flow. The paper focuses on safety engineering, an aspect which requires decision milestones due to standardized validation processes. It proposes a specific way to integrate safety constraints into a continuous and flowing process of Lean Product Development. To perform the safety integration in Lean Product Development, the proposed method simultaneously addresses process improvement of both product development and safety control. The proposal is a five-step method addressing the whole product development process from the requirements engineering step to the validation of the product prototype. This method was tested on an industrial case study and implemented into PLM TeamCenter.

In order to deal with global competition and increased customers expectation, companies must improve the efficiency of their manufacturing processes. Mainly, two approaches are available: the implementation of lean manufacturing practices and the deployment of information tools for data analysis. For a long time, these two strategies have been considered mutually exclusive; recently, it was understood that information concerning the manufacturing process is mandatory for the effective implementation of lean practices. This work aims at showing how Manufacturing Execution Systems (MES) can support the lean manufacturing paradigm into a medium size enterprise. The case study of a company in the supply chain of automotive components is presented to provide evidence about the role of MES and to highlight possible criticalities occurring during its implementation.

Current ICT developments in the areas of micro-devices, hardware infrastructure as well as internet and software technologies lead to a change of the physical products we know today. Traditional products are becoming smarter every day. The product generation meeting these innovations is called “Smart Products”. As a driver of the 4th industrial revolution these Smart Products will dominate most industrial sectors in the future. Product related data and the management of this data along the entire product lifecycle in the PLM context are becoming core components of these Smart Products. This is especially true for the tremendous amount of operational data generated by the Smart Products during their use phase. However, the management of Smart Products’ data related to a magnitude of heterogeneous product models (virtual product twins) will be crucial for the persistence of industrial companies. This paper illustrates that the virtual product twins have to be considered as integral components of Smart Products by giving concrete examples for the application of various virtual and physical products in different lifecycle phases.

To maintain market share rates, frugal innovation is a main solution for competitive enterprises to meet the customer’s needs in different regional markets. The co-evolution of product and production network aims to manage local production sites of the OEM and several collaborative relations between OEM and supplier companies for better management of the project resources in the regional market. Supplier selection and evaluation are among the main factors to be resolved at the earlier stage to guarantee successful results from any OEM-Supplier collaboration. This paper discusses the potential of using a modular-based approach as a kernel methodology to support the co-evolution of product structure and production network definition, especially in the case of supplier selection for frugal innovation perspective. The application of PLM approach to manage interconnected data describing the co-evolution of the product structure and production network is also discussed.

The Food and Beverage (F&B) industry has a unique role in all countries’ economies because it is essential to people lives. In this paper, the focus will be on the Italian food industry, one of the main food producer. This study will present the first results of a wider research that has as main aim to understand how PLM is adopted in the food industry, its limits and its challenges. Indeed, the first results show the level of knowledge of PLM systems in this sector, both from the literature and from the market point of view. Furthermore, the paper shows the results of a preliminary empirical research, made through several case studies, on the role of PLM in the product development process of the food industry.

Studying a product’s environmental impact on an interacted territory’s environmental status before and after design can increase decision makers’ accuracy when considering design for sustainability. Spatial representation of environmental information using Geographic Information Systems (GIS) is an approach to analyzing environmental status. This paper proposes a new data model to integrate geospatial data with product related data through environmental impacts over the whole lifecycle. This model uses coupling of GIS and PLM by ontology building. This new data model offers the possibility of enhancing sustainable products and obtaining more relevant results due to higher site specificity.

When it comes to Engineering-To-Order (ETO) products, neither the exact number nor the form of the components in them can be predefined. Thus, existing assembly models and generative design techniques are not adequate to support development of design automation tools for ETO products. ETO companies usually use custom libraries with past case designs that are adjusted to a customer’s requirements. This method is not cost effective and it is prone to human errors. In this work, we present the Automatic Assembly Synthesis Model (AASM), connecting a Knowledge Based Engineering (KBE) system and a CAD system to automate routine design tasks for ETO mechanical products.

During the design of experiments process several simulations and experimentations are performed to evaluate all design solutions’ alternatives. Technical meetings toke place regularly with the aim to select the product parameters and their values range to be considered in each simulation as well as the resolution methods and algorithms. One of the major problems concerns the lack of traceability and connections between all these design decisions and simulation results along the design process. A Simulation Data Management framework is proposed in this paper as a solution to resolve such kind of problems. This will enhance the final performance of the design of experiment process by reducing time of resolution and ensuring consistency of all simulation parameters, decisions and results.

Today, more than ever, enterprise interoperability is a key factor of successful collaboration and exchange of information. It was identified as a critical need that has to be taken into account through the whole life cycle of the manufactured product and an essential property for development and growth. This is particularly significant when it comes to collaborative enterprise networks, like Dynamic Manufacturing Network (DMN), where a distinct group of partners is connected in a chain-like model and where cooperation is crucial to achieve a specific goal. Dealing with interoperability issues in a collaborative DMN, we have to mention the importance of product data and process standards implementation as interoperability enablers. This work seeks to contribute to the improvement of enterprise interoperability along the manufacturing phase of the product in a collaborative DMN. It illustrates the collaboration between the business planning level and the manufacturing level with the implementation of PLM (Product Lifecycle Management) standards. Our added value is to follow a multi-level approach based on the use of standards in a DMN. The proposed approach is highlighted by a manufacturing case study.

Many projects and researches in the field of remanufacturing of specialized lathes are presented in the specialized literature. In the process of design for remanufacturing, a great number of solutions contain different aspects and data important to consider. The paper presents important stages of theoretical and applied research regarding the modernization of a conventional lathe with two working units by adaptation of four driving chains for CNC advance/positioning movements and improvements of translation couplings, adaptation of CNC equipment for driving and measuring simultaneous both wheels mounted on axle. The reducing of geometrical errors of the running profile is very important in reshaping the worn wheelsets. The lathe remanufacturing process involves the restoration of functional requirements and measurement of the geometric precision. The CNC capabilities of the remanufactured lathe require a database of parametric representation of profiles and rolling surfaces using CAD techniques according to international standards.

In medicine, the surgical instruments are realized using a variety of stainless steel, such as curved elevators. The quality and the price of surgical instruments differ in function of the manufacturing processes and the material used. This paper, presents a prototype of elevator, manufactured using two types of additive manufacturing process Direct Metal Laser Sintering – DMLS process for beaks and stereolithography process for the handles. The handle was made by means of stereolithography with the printer PROJET 1500, using a plastic material D638. The design and the quality obtained for the prototype of elevator is better, thanks to the material used and to the manufacturing process. The prototype of handle manufactured by stereolithography using the UV rays presents very good mechanical resistance and allows to be sterilized. For the handle of the elevator prototype there was performed a FEM analysis to identify stress locations and displacements. In this paper, was realized a Attenuated Total Reflection (ATR) analysis on the plastic material D638 to be examined directly in the solid state without further preparation.

In the use of ontologies to address semantic interoperability problems in PLM, either a lexicon or a list of synonyms of the terms in the domain are used to establish semantic mapping. This paper proposes a methodology to establish semantic equivalence of concepts with those in a given ontology based on some textual information about the new concept. This approach involves the classification of the information input into a structure form using natural language processing tools. Aircraft ontology available in literature, is taken as reference domain ontology for this purpose. Text input about the concept is parsed and the parts of speech (POS) tags are analyzed to obtain a structured representation. The structure is then compared to that in the domain ontology to decide if the input concept is part of the reference ontology and if so the concept it is equivalent to is identified. Results from an implementation of this procedure are shown and further work discussed.

Mobile devices have evolved rapidly in recent years and have become an everyday commodity. The young mobile PLM market is still in its infancy. At present, companies have covered their business processes with stationary workstations while mobile business applications have limited relevance and have been used to a limited extent. Companies can cover their overall business processes more time-efficiently and cost-effectively when they integrate mobile users in workflows. Mobile device features have the potential to significantly support the product development process through interactive user interactions and make them more effective. Moreover, entirely new workflows can be defined and established by considering mobile situations in business processes, which were excluded from the outset in the stationary context. This paper presents a novel approach for the usage of mobile device features in PDM systems to enhance user experience through novel interaction methods.

This paper focuses on the implementation of cloud solutions in the field of machining which is encompassed by the much larger field of manufacturing. Machining is the process of material removal to transform raw materials into final desired shape while manufacturing is the creation and assembly of components and finished products for sale. With the advent of new technologies, a lot of advancements have been made in the field of machining in the last few decades. We are seeing an explosive growth in the field of information technology and the world is more connected than ever before. The current scenario calls for manufacturers to change the way they perform operations by using cloud services rather than installing and customizing the softwares within their own organizations. This paper examines the intersection of the fields of machining and cloud computing to propose solutions for revolutionizing the way machining is done. After performing tests that involve machining simulations and creation of a collaborative working space to exchange data, we can conclude that it is completely feasible to perform machining operations on cloud. The findings of this study give an insight into the adoption of cloud technology in the machining field and provides useful information to industry professionals wishing to implement cloud solutions in their businesses and to scientists wishing to undertake work in this field.

Product model using Core Product Model (CPM) and its extension Open Assembly Model (OAM) has been implemented with cloud compatible open source technologies. Implementation focuses on data structure for capturing assembly hierarchy, part details, part features and feature associations. Super Constraint Tolerance Feature (SCTF) model has been used to extract information from STEP file. A case study on Cylinder cap assembly has been taken to showcase the data structure and classes. Entity Attribute Value (EAV) model has been used to manage and store the product metadata and product data. Parts and assemblies are defined as entities, product metadata as attributes and product data as values has been stored in separate tables. Methods to populate product model at different stages of design has also been discussed.

This paper proposes the use of liaison to develop a knowledge based system for variant design application to assist and guide designers at earlier stage of product development. A knowledge based framework has been proposed to support the joining process selection during variant design, where liaison act as an interface. Various liaison knowledge is represented in a complete and systematic manner. These liaison knowledge includes various geometric and non-geometric information. A user interface has been developed. A query engine is built and used to enable reasoning the joining process based on the requirement of a variant product. An industrial case study of two variants of automobile front bumper is provided in order to illustrate and validate the proposed knowledge based framework.

Products undergo through various processes in their lifecycle from production till use across the complex supply chain. Multiple actors are involved in these processes, generating ample amount of data. All the actors must share these data to make supply chain agile, effective and efficient to enhance the production control process. A traceability system companies use to trace these data. The current traceability system company use, is based on one step up and one step down principle, that is, immediate neighbouring actors share the information among themselves. No all the actors in supply chain share information among themselves which prevents collaboration. But, all these information are needed across the supply chain to enhance the quality of the product. In this work, we propose a global model for traceability to enhance the collaboration among every actors in supply chain with sharing of all the required information. Based on the model, we propose our data model.

The emergence of PLM for biomedical imaging lifecycle management highlights the needs for management and analysis of heterogeneous, complex and multidimensional data in PLM systems. Data provenance in biomedical imaging domain is complex, notably provenance of processing data, and to ensure full traceability in a purpose of reuse, processing operations must be integrated to PLM systems and processing provenance must be easily analyzable by users. The DIMP (Data Integrated Management and Processing) method was designed for this objective: it allows user to launch easily processing chains from PLM systems and ensures a full management of provenance. The MDG (Multidimensional Dynamic Graph) representation is introduced to formalize complex provenance and data relationships. JGEX (Json Graph EXchange) file format and NeuroGraphViewer web graph visualization client have been developed to facilitate the analysis of MDG. An application of the DIMP method to the study of functional brain connectivity through MDG analysis encourages further work on analysis of complex relationships in PLM systems.

Performance measurement represents one of the key lever to increase business competitiveness. Fashion companies are characterized by the centrality of products, so development and engineering should be monitored and controlled through proper performance measures. The goal of the entire study is to discuss how performance measurement is able to address and sustain the product development process within the fashion supply chain, considering also the involvement of PLM. A case study analysis has been conducted to select and validate the main measures related to product development and PLM.

Mobile manipulator performance measurement research is relatively minimal as compared to that of robot arms. Measurement methods, such as optical tracking systems, are useful for measuring the performance of mobile manipulators, although at a much higher relative cost as compared to artifacts. The concept of using test artifacts demonstrates to potential manufacturers and users of mobile manipulator systems that relatively low cost performance measurement methods exist. This paper discusses the concept of reconfigurable mobile manipulator artifacts that were designed and built. An artifact was then used through experimentation to measure the performance of a mobile manipulator to demonstrate the feasibility of the test method. Experimental results show a promising test method to measure the performance of mobile manipulators that are to be used for manufacturing assembly tasks, where at least the mobile manipulator tested has the capability to perform assembly to 1 mm positional accuracy or greater.

In the past few years, the architecture, engineering and construction (AEC) industry has carried out efforts to develop BIM (Building Information Modelling) facilitating tools and standards for enhanced collaborative working and information sharing. Lessons learnt from other industries and tools such as PLM (Product Lifecycle Management) – established tool in manufacturing to manage the engineering change process – revealed interesting potential to manage more efficiently the building design and construction processes. Nonetheless, one of the remaining challenges consists in closing the information loop between multiple building lifecycle phases, e.g. by capturing information from middle-of-life processes (i.e., use and maintenance) to re-use it in end-of-life processes (e.g., to guide disposal decision making). Our research addresses this lack of closed-loop system in the AEC industry by proposing an open and interoperable Web-based building lifecycle management system. This paper gives (i) an overview of the requirement engineering process that has been set up to integrate efforts, standards and directives of both the AEC and PLM industries, and (ii) first proofs-of-concept of our system implemented on two distinct campus.

This paper presents theoretical arguments for BIM ecosystem research, based on concepts of coevolution and emergence in a complex network of constituent elements: products, processes, people, technology and policies. Broader trends such as Internet of Things, data analytics, and digital manufacturing are increasingly becoming integral to BIM systems. Consequently BIM research is evolving along multiple pathways. Therefore, there is need for methodologies and approaches to analyze BIM ecosystem. Three types of ecosystem analyses are proposed: (1) BIM-Ecosystem Retrospective Analysis (BIM-ERA), to understand the ecosystem’s constituents and their dependencies, based on facts and history, (2) BIM-Ecosystem Feasibility analysis (BIM-EFA), to be able to use the knowledge of the constituents and their dependencies to assess whether an intended intervention in a given ecosystem is feasible or not, and (3) BIM-Ecosystem Impact Analysis (BIM-EIA), to be able to conduct what-if studies to assess the potential short-term and long-term impact of a potential action.

The increasing use of Building Information Modelling (BIM) across the construction industry highlights the potential for a common endpoint with manufacturing industries. Previous research work has shown that it is possible to improve BIM with the features and the best practices from Product Lifecycle Management (PLM) approach. This article provides a comparison between the PLM and BIM approaches from the standpoint of the Product Structure (PS) and the Bill of Material (BOM). It discusses the need to explicit a structuring concept in the BIM approach in order be able to switch to an information-centric management approach in construction projects instead of the current activity-based approach.

The product use data can have an important role in closed-loop product lifecycle management (CL-PLM), where information feedbacks from the use data can contribute to improve the product design and performance. The product usage data can nowadays be collected easier than before, with the aid of sensors and technologies embedded in products. However, the collected data can have complex characteristics. They come from various sources, have different formats and high volume. In order to improve the product lifecycle processes with these data, discussing the use of data analysis in the product lifecycle is necessary. Analyzing the data with such characteristics has been also considered in the context of big data analytics. In this paper an approach for standardization of the process of usage data analysis based on a standard called Cross Industry Standard Process for Data Mining (CRISP-DM), is introduced and its potential integration in CL-PLM is investigated. The reference steps of analyzing usage data are identified. They cover the processes between data generation until feeding back the knowledge of use to the product design phase.

Big data analytics enables organizations to process massive amounts of data in shorter amounts of time and with more understanding than ever before. Many uses have been found to take advantage of this tools and techniques, especially for decision making. However, little applications have been found in the first stages of innovation, namely problem definition and idea generation. This paper discusses how big data analytics can be utilized in those stages. It includes an example of application in problem definition and proposes a case study implementation in a higher education setting for idea generation.

Mechanical Reverse Engineering has been getting increasingly more attention from the industry. It aims rebuilding a broad Digital Mock Up (DMU) in order to redesign and/or remanufacture a product. Some of the reverse engineering challenges are to perform an efficient knowledge extraction out of the original product, and then to process the data it and consolidate them for further analysis. These data could be extracted from a vast number of different data as such as Manufacturing Data, Technical Reports, Design Data (e.g. CAD Files, technical drawings, etc.), Quality procedures, etc. Moreover, the amount of data stored by the companies’ information system keep on rapidly growing. We propose to use data science in order to cope with the previous issues. This paper aims to detail the different possibilities offered by the data science field of expertize, more precisely in terms of machine learning, text mining and computer vision, but also to give a brief overview on the future works we will research. This paper position itself as a roadmap for our further proceedings.

Different recent approaches from the Product Lifecycle Management (PLM) or Internet-of-Things (IoT) area describe a product-centric view on data and information which are collected by different stakeholders and systems along the lifecycle in order to enhance retrospective analytics, predictive analytics, business decisions, etc. The purpose of this paper is to investigate the basic principles of information sharing, communication and collaboration in traditional human-centric social networks and discuss whether these can be applied to data and information exchange in the PLM/IoT sector. With respect to the methodology applied to this investigation, recent communication mechanisms in social networks as well as in product-centric IoT platforms are systemized and abstracted. Based on the transformation of social network means for IoT, possible improvements of IoT platforms are discussed, resulting in demonstrations of possible PLM usage. In summery, the paper draws implications about the adoption of valuable Social Network means for product-centric usage.

Currently, Internet of Things (IoT) is a dominant technology and a core mechanism for the third Information Technology (IT) revolution. Many benefits are expected to be enabled by implementing the IoT technologies through the product lifecycle management (PLM) process, such as remote monitoring of field service and predictive quality reliability engineering design in R&D. Smart connected products (SCPs) are forecast to produce tremendous business value. However, significant business challenges are associated with SCPs. Manufacturers have difficulty in rapidly launching IoT products in the market. This paper proposes a pragmatic visioneering workshop framework informed by real-world industry practices. The group facilitation for visioneering focuses on identifying the relation between the 26 practical IoT use cases through the PLM process. Moreover, the proposed workshop format will also enable the participants to engage in a discussion and interact with the framework through use case analysis.

In 2012, our research team in partnership with LASCOM (a French PLM software editor) proposed models and an approach to help SMEs when they decide to deploy PLM systems [1, 2]. Our approach was to use formalism based on mind maps to promote exchanges between customer/users and PLM editor. Objective was to facilitate definition of elements that have to be defined, modeled, evaluated and implemented in a software solution to make deployment process more effective. Different real case studies emphasized that our approach have to evolve to be more “customer” centered. In this paper we present one of these real case studies which is in progress. This research collaboration concerns POULT, a manufacturer of biscuits which decided to deploy a PLM solution in few months. We describe the adopted approach to analyze the users’ needs and draft the request for proposal which will be send to PLM editors.

Intralogistics systems secure the internal flow of materials and are a success factor for handling and producing companies. In general, the objective of analysing life-cycle costs is to economically evaluate system design alternatives aiming at supporting investment decisions. One essential influence factor of operating costs, and thus life-cycle costs, is the availability. The non-availability significantly influences the operating costs, e.g. repairs or loss of revenues. A research field that has not been investigated in the field of intralogistics is the monetarisation of non-availability. An appropriate cost model is therefore necessary. As a result, the costs of non-availability can be evaluated monetarily as a function of time. With the help of such a monetary parameter, financial risks can already be detected during the planning phase. This paper models an approach of the monetarisation of the non-availability of intralogistics systems as an economical evaluation indicator during the planning phase.

The purpose of this paper is to collect and structure the various features of Smart Manufacturing (SM). Researchers have previously identified various characteristics and technologies of Smart Manufacturing System (SMS); this paper collects, discusses and merges some of those characteristics and technologies available in the current body of knowledge. In the future, it is expected that this selection of characteristics and technologies will help to compare and distinguish other initiatives like Industry 4.0, smart factory, intelligent manufacturing, distributive manufacturing, etc. which are frequently used synonymous with SM. The result of this paper is a comprehensive list of characteristics and technologies that are associated with a SMS. As many of the listed items show variating overlaps, certain technologies and characteristics are merged and clustered. This results in a set of five defining characteristics and ten technologies that are considered relevant for a SMS. The authors hope to provide a basis for a broad and interdisciplinary discussion within the SM community about the defining technologies and characteristics of a SMS.

This paper addresses the data, information and knowledge management challenges in product lifecycle management (PLM) using novel industrial internet/industry 4.0/cyber-physical system platforms. PLM is quite seminally related to data, information and knowledge, and about getting these properly to serve a company’s business and product development as well as to create value for the customer. We analyze Industry platforms, that are enabled by industrial internet based technologies as well as certain collaboration and social media platforms that help solving certain PLM challenges. This analysis will allow companies to make informed decisions while selecting platforms to solve their PLM challenges.

This is a position paper to share our experience how Lazy Evaluation approach in AI is useful for team decision making with members with diverse knowledge and experience from many different fields. For example, Industrie 4.0 is a German proposal of a new framework to team up SMEs in order to cope with the frequent and extensive changes today. Until recently, we could fight with 11 best players, but today we need to fight with best 11. If the situations do not change then best players in each position can form a good team and win. But just as soccer demonstrates, such fixed formation does not work anymore. All players have to changes their roles flexibly and adaptively in response to the change. But unlike soccer where a goal is very clear, engineering teams need to determine a common goal first of all. But the greatest difficulty is members have different knowledge and experience, especially so when members come from different fields. Thus, how we can coordinate their diverse scopes and come up with an identical scope which satisfy all members and which leads to fruitful collaboration is a big challenge. This paper describes how Lazy Evaluation is effective for negotiation among members with diverse knowledge and experience and for coming up with an identical goal toward fruitful collaboration.

With the understanding of the enormous economic value inherent in next generation products, business enterprises repeatedly describe the value metrics and Return On Investment (ROI) of Product Lifecycle Management (PLM) as difficult to assess, thus confounding their ability to quickly and strategically make decisions. Given that PLM initiatives are such sizable investments and interdisciplinary, executives are struggling to agree upon value metrics to measure throughout the project to understand an accurate value created. Thus a shortage of known ROI information is available to make the case for financing a PLM project; moreover unique industry and organizational variables make it unfeasible for companies to easily benchmark competitors and predetermine the values gained. A literature review reveals a void of information relative to quantifiable value metrics and ROI of PLM. This article proposes a framework to use Grounded Theory research methodology to capture value metrics and formulate models, contributing to future organizational decisions on PLM implementations.

PLM encompasses a wide array of expertise, from designing green products to digital factories, with perspectives ranging from an IT standpoint to business strategies, encompassing products, processes and services. Hence, identifying the contours of PLM as a science through the themes, trends and clusters of its scientific literature is very challenging. At the same time, being able to portray PLM will benefit the PLM community, including researchers and practitioners, and should help foresee its future. This work examines PLM research bibliometric trends over the last ten years. We review the scientific literature published in English from 2005 to 2014 in peer-reviewed journals and conferences. Paper keywords are analyzed so as to identify trends and reveal the clusters of related themes based on the occurrences of words and the frequency of associations between them. Amongst the findings we observe that PLM coverage is both very large (2847 keywords being used over a decade) and very thin (2134 of these keywords appear only once in the decade). We also observe that the keyword showing the highest increase is Building Information Modeling (BIM).

CyberManufacturing System (CMS) is an advanced vision for future manufacturing where physical components are fully integrated and seamlessly networked with computational processes, forming an on-demand, intelligent and communicative manufacturing resource and capability repository with optimal, sustainability-oriented manufacturing solutions. CMS utilizes recent developments in Internet of Things, Cloud Computing, Fog Computing, Service-Oriented Technologies, etc. Manufacturing resources and capabilities can be encapsulated, registered and connected to each other directly or through the Internet, thus enabling intelligent behaviors of manufacturing components and systems such as self-awareness, self-prediction, self-optimization, and self-configuration among others. This research presents a definition of CMS, an architecture and unique functions of CMS, and performance analysis of CMS using simulation models. Five examples have been developed and used for illustration and validation of CMS. The results show significant improvement in enhanced functionality and cooperative performance.

Product lifecycle is a complex network with large supply chains from multiple organisations. Lifecycle assessment of products of organisations with globally dispersed manufacturing supply chains and international market involves various spatial and temporal constraints. Even though organisations have data of their global supply chains, data is typically stored textually as spreadsheets, or visually as process flow charts. Visual representation of this large data using flow charts makes it complex and difficult to read and interpret. A decluttered, simplified product lifecycle data representation method is presented in this paper, which is developed for use alongside an LCA tool.

The producers of marine auxiliaries face the challenge, that they need to adapt their middle-of-life activities to the otherwise defined and often not well communicated schedules of the ships, which are carrying their products. This paper presents both the methodological approach to a solution and its prototypical implementation in a specific use case. The solution presented is utilizing the Internet of Things (IoT) and the data that is constantly being produced by the ships through the Automatic Identification System (AIS) to help overcome this problem.

Lifecycle management enables enterprises to manage their products, services and product-service bundles. IoT and CPS have made products and services smarter by closing the loop of data across different phases of lifecycle. Similarly, CPS and IoT empower cities with real-time data streams from heterogeneous objects. Yet, cities are smarter and more powerful when relevant data can be exchanged between different systems across different domains. From engineering perspective, smart city can be seen as a System of Systems composed of interrelated/interdependent smart systems and objects. To better integrate people, processes, and systems in the smart city ecosystem, this paper discusses the use of Lifecycle Management in the smart city context. Considering the differences between ordinary and smart service systems, this paper seeks better understanding of lifecycle aspects in the smart city context. For better understanding, some of the discussed lifecycle aspects are demonstrated in a smart parking use-case.

One of the aspects of a good inventory control system is low Inventory Record Inaccuracy (IRI). IRI control ought to be an integral part of PLM by helping to further streamline the production, transportation and service stages. This paper contributes to the expanding debate on linking error generation to Inventory Record Inaccuracy (IRI) and its ensuing effects on performance. Methods of discovering and eliminating the root causes of IRI are presented. A System Dynamics (SD) simulation model is used to examine and confirm the substantial impact of error generation and IRI on workflow. The results of the model show that even a small undetected source of IRI can accumulate and eventually destabilize the entire system.