A bibliographic review of production line design and balancing under uncertainty

This bibliography reviews the solution methods developed for the design and balancing problems of production lines such as assembly and disassembly lines. The line design problem aims in determining the number of workstations along with the corresponding assignment of tasks to each workstation, while the line balancing problem seeks an assignment of tasks, to the existing workstations of the line, which ensures that the workloads are as equal as possible among the workstations. These two optimisation problems can be also integrated and treated as a multi-objective optimisation problem. This review considers both deterministic and stochastic formulations for disassembly lines and is limited to assembly line design and balancing under uncertainty. This bibliography covers more than 90 publications since 1976 for assembly and 1999 for disassembly

Research Trends and Outlooks in Assembly Line Balancing Problems

This paper presents the findings from the survey of articles published on the assembly line balancing problems (ALBPs) during 2014-2018. Before proceeding a comprehensive literature review, the ineffectiveness of the previous ALBP classification structures is discussed and a new classification scheme based on the layout configurations of assembly lines is subsequently proposed. The research trend in each layout of assembly lines is highlighted through the graphical presentations. The challenges in the ALBPs are also pinpointed as a technical guideline for future research works

Balancing and Sequencing of Mixed Model Assembly Lines

Assembly lines are cost efficient production systems that mass produce identical products. Due to customer demand, manufacturers use mixed model assembly lines to produce customized products that are not identical. To stay efficient, management decisions for the line such as number of workers and assembly task assignment to stations need to be optimized to increase throughput and decrease cost. In each station, the work to be done depends on the exact product configuration, and is not consistent across all products. In this dissertation, a mixed model line balancing integer program (IP) that considers parallel workers, zoning, task assignment, and ergonomic constraints with the objective of minimizing the number of workers is proposed. Upon observing the limitation of the IP, a Constraint Programming (CP) model that is based on CPLEX CP Optimizer is developed to solve larger assembly line balancing problems. Data from an automotive OEM are used to assess the performance of both the MIP and CP models. Using the OEM data, we show that the CP model outperforms the IP model for bigger problems. A sensitivity analysis is done to assess the cost of enforcing some of the constraint on the computation complexity and the amount of violations to these constraints once they are disabled. Results show that some of the constraints are helpful in reducing the computation time. Specifically, the assignment constraints in which decision variables are fixed or bounded result in a smaller search space. Finally, since the line balance for mixed model is based on task duration averages, we propose a mixed model sequencing model that minimize the number of overload situation that might occur due to variability in tasks times by providing an optimal production sequence. We consider the skip-policy to manage overload situations and allow interactions between stations via workers swimming. An IP model formulation is proposed and a GRASP solution heuristic is developed to solve the problem. Data from the literature are used to assess the performance of the developed heuristic and to show the benefit of swimming in reducing work overload situations

Assembly Line

An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line

Best matching processes in distributed systems

The growing complexity and dynamic behavior of modern manufacturing and service industries along with competitive and globalized markets have gradually transformed traditional centralized systems into distributed networks of e- (electronic) Systems. Emerging examples include e-Factories, virtual enterprises, smart farms, automated warehouses, and intelligent transportation systems. These (and similar) distributed systems, regardless of context and application, have a property in common: They all involve certain types of interactions (collaborative, competitive, or both) among their distributed individuals—from clusters of passive sensors and machines to complex networks of computers, intelligent robots, humans, and enterprises. Having this common property, such systems may encounter common challenges in terms of suboptimal interactions and thus poor performance, caused by potential mismatch between individuals. For example, mismatched subassembly parts, vehicles—routes, suppliers—retailers, employees—departments, and products—automated guided vehicles—storage locations may lead to low-quality products, congested roads, unstable supply networks, conflicts, and low service level, respectively. This research refers to this problem as best matching, and investigates it as a major design principle of CCT, the Collaborative Control Theory. The original contribution of this research is to elaborate on the fundamentals of best matching in distributed and collaborative systems, by providing general frameworks for (1) Systematic analysis, inclusive taxonomy, analogical and structural comparison between different matching processes; (2) Specification and formulation of problems, and development of algorithms and protocols for best matching; (3) Validation of the models, algorithms, and protocols through extensive numerical experiments and case studies. The first goal is addressed by investigating matching problems in distributed production, manufacturing, supply, and service systems based on a recently developed reference model, the PRISM Taxonomy of Best Matching. Following the second goal, the identified problems are then formulated as mixed-integer programs. Due to the computational complexity of matching problems, various optimization algorithms are developed for solving different problem instances, including modified genetic algorithms, tabu search, and neighbourhood search heuristics. The dynamic and collaborative/competitive behaviors of matching processes in distributed settings are also formulated and examined through various collaboration, best matching, and task administration protocols. In line with the third goal, four case studies are conducted on various manufacturing, supply, and service systems to highlight the impact of best matching on their operational performance, including service level, utilization, stability, and cost-effectiveness, and validate the computational merits of the developed solution methodologies

Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Copyright © 2014 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 31 January 2014, available online: http://www.tandfonline.com/10.1080/00207543.2013.879618Growing interests from customers in customised products and increasing competitions among peers necessitate companies to configure their manufacturing systems more effectively than ever before. We propose a new assembly line system configuration for companies that need intelligent solutions to satisfy customised demands on time with existing resources. A mixed-model parallel two-sided assembly line system is introduced based on the parallel two-sided assembly line system previously proposed by Ozcan et al. (Balancing parallel two-sided assembly lines, International Journal of Production Research, 48 (16), 4767-4784, 2010). The mixed-model parallel two-sided assembly line balancing problem is illustrated with examples from the perspective of simultaneous balancing and sequencing. An agent based ant colony optimisation algorithm is proposed to solve the problem. This algorithm is the first attempt in the literature to solve an assembly line balancing problem with an agent based ant colony optimisation approach. The algorithm is illustrated with an example and its operational procedures and principles explained and discussed

An Experimental Research on Closed Loop Supply Chain Management with Internet of Things

Abstract. Closed loop supply chain (CLSC) optimization is integration of forward and reverse logistics activities. The importance of CLSC management is increasing by legal regulations, limited energy resources and environmental- financial problems that growing in recent years. However, reverse logistics part of the CLSC is a flow type which is more difficult to made predictions, planning and controls by reason contained uncertainties. This stage, Internet of Things system reduces related uncertainties by providing all the life information of the returned product and substantially attenuates planning of reverse flow activities. In this study, a CLSC is considered that meets demands of the sales&collection center both new and remanufactured product. Manufacturer has three options (refurbishing, disassembly and disposal) to assessing returned products. A mixed integer linear programming model is proposed for a single type of product is completely modular (automobile, computer, telephone, etc.). The model meets customer's products and components demands based period, maximizes profit consist of different sales revenues and total cost (total production, purchase, transportation and disposal costs) and determines how to evaluate all returned products. The proposed model has been verified with the aid of a numerical example by solving in GAMS software and its performance reviewed with experimental studies.Keywords. Closed loop supply chain optimization, Internet of Things, Mixedinteger linear programming, Returned product management.JEL. L80, L86, Q55