Review
A review of cost and profit oriented line design and balancing problems and solution approaches

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Abstract

This review paper presents the state of the art on the problems, approaches and analytical models for assembly and transfer line design and balancing that addresses explicitly cost and profit oriented objectives. The discussions aim to facilitate identifying open problems and research areas that have wide practical applications and that necessitate further investigations. Moreover, they might serve as a foundation for developing decision support systems (DSS) that aid managers in planning and designing profitable or cost efficient assembly and transfer lines.

Introduction

Assembly and transfer lines contain serially located workstations in which the operations are continuously carried out. They have been installed in various industries such as the automotive, home appliance or electronics, where the major goal is to efficiently produce and deliver large amounts of standardized products. As a consequence of efficiency pursuit of these industries, modeling and solving line balancing problems have gained importance. A rich assembly and transfer line balancing literature, which covers numerous optimization problems, emerged.

These problems require development of capacity or cost-based modeling and use of effective solution techniques. For more details on line balancing problems, modeling and solution methods, we refer to the survey papers, such as Ghosh and Gagnon (1989), Erel and Sarin (1998), Rekiek, Dolgui, Delchambre, and Bratcu (2002), Becker and Scholl (2006), Scholl and Becker (2006), Boysen, Fliedner, and Scholl (2008a) and Rashid, Hutabarat, and Tiwari (2012). We also cite Boysen, Fliedner, and Scholl (2007) and Battaia and Dolgui (2013) for classification of the problems.

Although these interesting surveys present a broad range of line balancing problems and methods, they do not provide an in-depth analysis of some important branches of line design and balancing literature. This lack is noticeable for cost and profit based models, despite their recognized importance (see, e.g., Falkenauer, 2005). One possible explanation could be the scarcity (at the time these surveys were written) of publications on this topic, in comparison with other branches which had produced an abundant literature. Even though capacity oriented approach is more common in the literature, models where costs and profits are explicitly calculated and optimized in all phases of product life cycle are taking attention of researchers. Studies on this field have been rapidly increasing recently (almost half of the papers cited in this review were published during the last 8 years).

We concentrate on this particular branch and provide an in-depth analysis of cost and profit based line design and balancing models. Such a detailed study allows us to investigate the use of optimization tools in the design of production facilities, to explain their needs in planning and control of activities, from product and process design to recycling, and to clarify their characteristics and importance for product life cycle management (PLM).

It should also be noted that most of the models presented in this survey require various data on costs in order to produce cost-efficient line balance. It might not be always possible to have reliable cost figures at the point in time line balancing is performed. Thus, often researchers fall back on simple performance criteria of the capacited models, which are available, e.g., the number of stations or the cycle time. Moreover, under specific premises some simple line balancing problems also minimize costs, e.g., the capacity oriented Simply Assembly Line Balancing Problem of type 1 (SALBP-1) leads to a cost minimum, whenever any station costs the same. Also minimizing the cycle time for the capacity oriented Simply Assembly Line Balancing Problem of type 2 (SALBP-2) could maximize profit in specific circumstances.

However, nowadays many companies can reach to accurate data, they are more and more seeking to use this information and generate more effective designs. We also note that cost and profit based models are usually used at advanced stages of the design process. At the initial stages, a set of possible configurations is selected by using capacity oriented models. Cost- or profit- oriented approach is employed afterwards.

Considering the increase in the number of publications on cost- and profit-oriented models, we believe that it has become necessary to structure this field and develop a more detailed classification. Moreover, we make a concerted effort to present research gaps and explicitly list promising areas. We discuss the possible research perspectives. The discussion could help to identify open problems and research areas that have wide practical applications and need further investigation.

This article is an expanded and improved version of the paper presented at the 19th World Congress of the International Federation of Automatic Control in Cape Town, South Africa (Hazir, Delorme, & Dolgui, 2014).

Section 2 will introduce the classification and then review and discuss the main publications in each class. Section 3 will present a synthesis of this review and provide some discussions on future research directions.

Section snippets

Literature review

Cost based models minimize long-term investment or short term operating costs, whereas in profit based models revenues hence price and production volumes are also incorporated. Main relevant cost categories that should be examined are wages, material and inventory expenses, equipment procurement and maintenance, setup and idle time costs and the penalties of delays.

Some cost or profit based models optimize objective functions that include components concerning productivity or efficiency, which

Conclusions and future research directions

We summarized the existing cost and profit based research studies in Tables 1 and 2. The first table presents studies which addressed a single category, However the second table focuses on the ones that examined multiple cost categories. In both of the tables, the first column refers to the cost or profit, whereas the second to the relevant studies addressed.

Examining the tables we conclude that equipment costs took attention of many researchers. Studies that examine other cost categories or

Acknowledgments

This work was partially supported by the European Commission 7th Framework Project ‘Advanced Platform for Manufacturing Engineering and Product Lifecycle Management’ (AmePLM), project number 285171.

Öncü Hazır is currently working as an Associate Professor in TED University in Ankara. He received his bachelors’ degree in Industrial Engineering in 1999 and master degree in business administration in 2001 from Middle East Technical University, Ankara, Turkey. He prepared a dissertation in project scheduling in Bilkent University where he obtained a Ph.D. in operations management in 2008. During his studies, he gave courses such as scheduling, statistics, production planning and control in

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    Öncü Hazır is currently working as an Associate Professor in TED University in Ankara. He received his bachelors’ degree in Industrial Engineering in 1999 and master degree in business administration in 2001 from Middle East Technical University, Ankara, Turkey. He prepared a dissertation in project scheduling in Bilkent University where he obtained a Ph.D. in operations management in 2008. During his studies, he gave courses such as scheduling, statistics, production planning and control in Çankaya University Industrial Engineering Department. He worked as a post-doctorate researcher at Laboratoire d’Informatique de Paris 6 and Ecole des Mines de Saint-Etienne in France between 2009 and 2012. He participated in various research activities in project management and control, machine scheduling and assembly line balancing. He published several papers in various operations research journals.

    Xavier Delorme is an Associate Professor at the Ecole des Mines de Saint-Etienne (France) and Deputy Director of the Laboratory of Computer Science, Systems Modeling and Optimisation (LIMOS, UMR CNRS 6158). His research focuses on Operations Research models for production line design, supply chain optimization and railway transport. He is the author of 20 refereed journal papers and 4 book chapters as well as over 40 papers in conference proceedings. He is a Member of the Editorial Board of the Mathematical Problems in Engineering journal.

    Alexandre Dolgui is a Distinguished Professor and the Head of Automation, Production and Computer Sciences Department at the Ecole des Mines de Nantes, France. His research focuses on manufacturing line design, production planning and supply chain control and optimization. His main results are based on the exact mathematical programming methods, control theory and their intelligent coupling with heuristics and metaheuristics algorithms. He is the co-author of 5 books, the co-editor of 15 books or conference proceedings, the author of more than 200 refereed journal papers, editorials and book chapters. He is the Editor-in-Chief of the International Journal of Production Research, an Area Editor of Computers & Industrial Engineering, and an Associate Editor of Journal Européen des Systèmes Automatisés, past Associate Editor of International Journal of Systems Science, IEEE Transactions on Industrial Informatics and Omega, consulting Editor of the International Journal of Systems Science. He is a Member of the Editorial Boards for 22 other journals, including the International Journal of Production Economics. Dr. Dolgui is Chair of IFAC Technical Committee 5.2 Manufacturing Modelling for Management and Control, as well as a Fellow of the European Academy for Industrial Management, Member of the Board of the International Foundation for Production Research, Member of IFIP WG 5.7 Advances in Production Management Systems, Member of IEEE System Council Analytics and Risk Technical Committee. Dr. Dolgui has obtained several international and national awards for his research.

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