Incorporating human resources in group technology/cellular manufacturing

In today's fiercely competitive marketplace, firms are looking for ways to improve their profitability. Computer simulation studies comparing group technology/cellular manufacturing (GT/CM) to job-shop layouts addressed this topic. However, each study ignored some of the most basic operating conditions said to give GT/ CM its advantages: this simulation study incorporates some of those operating conditions like human resource issues, such as learning and labour constraints, in a comprehensive setting. The results indicate that GT/CM significantly outperforms the job shop layout in almost every environmental setting.     

A comparison of focused cellular manufacturing to cellular manufacturing and job shop

The purpose of this study is to compare a focused cellular manufacturing environment with traditional cellular manufacturing, and job shop environments. We define focused cellular manufacturing as a configuration scheme that groups components by end-items and forms cells of machines to fabricate and assemble end-items. In addition, this research includes three levels of batch sizes and two levels of set-up times in its performance criteria which few researchers in this area have done. The results indicate that the focused cellular manufacturing scheme has a batching advantage. This advantage dominated the balanced machine utilization benefit of the job shop configuration scheme and out weighed the set-up time reduction advantage of the cellular manufacturing scheme for average end-item completion times and average work-in-process inventory levels. The cellular manufacturing and job shop schemes overcame the batch size advantage only when batch sizes were small or set-up times were large.     

Multiperiod tool and production assignment in flexible manufacturing systems

Flexible manufacturing systems (FMSs) are usually composed of general purpose machines with automatic tool changing and integrated material handling. FMSs offer the advantages of high utilization levels and simultaneous production of a variety of part types with minimal changeover time. Although the trend in FMS operation appears to be towards unmanned production, there is much diversity in the policies under which FMSs can be operated. These policies are governed to some extent by the available technological resources. In this paper several policies are described. Tool loading and production assignment models for setting production plans over a short term planning horizon when using these policies are then formulated. Heuristics for the solution of these models are detailed and computational results are presented.     

Task assignment considering cross-training goals and due dates

When a worker performs a task at which he is not fully experienced, he is increasing his future performance in doing this task. Thus, task assignment can consider objectives regarding task accomplishment and objectives regarding cross-training. The contribution of this paper lies in presenting and modelling the assignment of a set of tasks to a set of workers considering cross-training goals and that some of the tasks have to be completed at given due dates. The influence of the experience of one task on the performance on other tasks is taken into account. The model allows (1) testing the feasibility of a given combination of cross-training goals and due dates; (2) obtaining the task assignment that maximises the total work done – considering the tasks that have a due date and the tasks that do not; and (3) calculating the change on the total quantity of work performed because of the establishment of cross-training goals or due dates. A computational experiment is carried out by using MILP optimisation software.     

Dynamic cellular manufacturing system design considering alternative routing and part operation tradeoff using simulated annealing based genetic algorithm

In this paper, an integrated mathematical model of multi-period cell formation and part operation tradeoff in a dynamic cellular manufacturing system is proposed in consideration with multiple part process route. This paper puts emphasize on the production flexibility (production/subcontracting part operation) to satisfy the product demand requirement in different period segments of planning horizon considering production capacity shortage and/or sudden machine breakdown. The proposed model simultaneously generates machine cells and part families and selects the optimum process route instead of the user specifying predetermined routes. Conventional optimization method for the optimal cell formation problem requires substantial amount of time and memory space. Hence a simulated annealing based genetic algorithm is proposed to explore the solution regions efficiently and to expedite the solution search space. To evaluate the computability of the proposed algorithm, different problem scenarios are adopted from literature. The results approve the effectiveness of the proposed approach in designing the manufacturing cell and minimization of the overall cost, considering various manufacturing aspects such as production volume, multiple process route, production capacity, machine duplication, system reconfiguration, material handling and subcontracting part operation.     

Designing a cellular manufacturing system considering decision style,skill and job security by NSGA-II and response surface methodology

Cell formation is a traditional problem in cellular manufacturing systems that concerns the allocation of parts, operators and machines to the cells. This paper presents a new mathematical programming model for cell formation in which operators’ personality and decision-making styles, skill in working with machines, and also job security are incorporated simultaneously. The model involves the following five objectives: (1) minimising costs of adding new machines to and removing machines from the cells at the beginning of each period, (2) minimising total cost of material handling, (3) maximising job security, (4) minimising inconsistency of operators’ decision styles in cells and (5) minimising cost of suitable skill. On account of the NP-hard nature of the proposed model, NSGA-II as a powerful meta-heuristic approach is used for solving large-sized problems. Furthermore, response surface methodology (RSM) is used for tuning the parameters. Lastly, MOPSO and two scalarization methods are employed for validation of the results obtained. To the best of our knowledge, this is the first study that presents a multi-objective mathematical model for cell formation problem considering operators’ personality and skill, addition and removal of machines and job security.     

Models for machine-part grouping in cellular manufacturing

For cellular manufacturing strategies to succeed, the productive system first has to be divided into highly independent cells. This means that a partition of the machines into machine groups, a partition of the parts into part families, and a matching between the machine groups and the part families have to be simultaneously determined. Mathematically, this question can be expressed as the problem of finding a near block diagonal permutation of the machine-part incidence matrix. Research on such grouping problems has primarily concentrated on the design of heuristics. Different grouping efficiency criteria have been proposed to express the quality of the groupings proposed by these heuristics. This paper is concerned with mathematical programming approaches to the formation of production cells. Existing models are reviewed and their features are briefly discussed. An alternative model is proposed, which allows for the formulation of various constraints and grouping efficiency criteria. Finally, some test problems are used to support the claim that this model may be adequate for the solution to optimality of the cell formation problem.     

Optimal resource assignment through negotiation in a multi-agent manufacturing system

Research studies on multi-agent systems have been recently boosted by manufacturing and logistics with deep motivations like the presence of independent human deciders with individual goals, the aspiration to dominate the complexity of decision-making in large organizations, the simplicity and robustness of self-reacting distributed systems. After a survey of the multi-agent paradigm and its applications, the paper introduces the notion of hybrid holonic system to study the effect of supervision on a system whose elements negotiate and cooperate in a rule-settled environment to obtain resources for system operation. The supervisor can spur or disincentive agents by assigning/denying resources to them. A simple single-decider optimization model referred to a real application is described, and solution methodologies for optimal resource allocation fitting different scenarios (centralized, distributed, multi-agent) are discussed, identifying ranges of autonomy, quantifying rewarding and defining a negotiation protocol between the agents and the supervisor. Aim of the paper is to describe through an example a general methodology for quantitative decision-making in multi-agent organizations.     

Optimal job assignment considering operators’ walking costs and ergonomic aspects

The paper deals with the problem of assigning jobs to operators in contexts where the operators are not fixed on a single position, but rotate, by travelling on foot, between different stations. The objective is to jointly consider the need for minimising the operators’ walking costs, expressed as both unproductive times and physiological costs, and the ergonomic risk of the scheduled jobs and their combinations. A new optimisation-based methodology is presented by developing a systematic procedure for input data analysis and an original mixed-integer linear programming model which minimises the cost of walking (or the total metabolic cost) by considering workplace safety and physiological needs. Finally, the proposed optimisation approach has been applied to a case study from the plastic industry. The obtained results allow to draw some interesting conclusions about the impact of ergonomic aspects on the optimal assignment of jobs to operators. Moreover, the importance of reducing unproductive times (i.e. walking times) and, if possible, improving the design of manual tasks (e.g. lifting operations) is highlighted by showing that even small ergonomic investments may lead to significant cost savings.     

Performance comparison of virtual cellular manufacturing with functional and cellular layouts in DRC settings

This study investigates the performance of virtual cellular manufacturing (VCM) systems, comparing them with functional layouts (FL) and traditional, physical cellular layout (CL), in a dual-resource-constrained (DRC) system context. VCM systems employ logical cells, retaining the process layouts of job shops. Part family-based scheduling rules are applied to exploit the benefits of group technology while retaining the flexibility and functional synergies of the job shop. Past studies of VCM have been based entirely on single-resource-constrained (SRC) systems, i.e. as purely machine-limited systems, assuming that resources such as labour and tooling do not restrict the output. However, given the fact that labour forms a second major constraining resource, and many of the advantages associated with cellular manufacturing are derived from labour flexibility, it becomes necessary to extend the research to DRC systems. In this study, we assume several levels of labour flexibility in all three systems, in addition to other relevant factors such as lot size, set-up reduction, and labour assignment rules. It is shown that VCM can outperform efficiently operated FL and CL in certain parameter ranges, as preliminary research has shown so far. However, it is shown that CL tends to outperform both VCM and FL in the parameter ranges customarily advocated for CL, namely, low lot sizes, adequate levels of set-up reduction, cross training of workers, and worker mobility within cells.     

Learning and labour assignment in a dual resource constrained cellular shop

Recent studies have shown that in a cellular shop that benefits from learning due to repetitive processing, limitations attributable to routing flexibility can be more than offset. Moreover, the shop can respond more quickly to changes in demand than a job shop. This study examines the impact of labour assignments in a dual constrained cellular shop in which processing times decrease with operator task repetition. Results indicate that in the presence of operator learning, shop performance is significantly affected by the flexibility permitted in labour assignments. Moreover, the sensitivity of performance to labour assignments is significantly impacted by staffing levels and the magnitude of learning effects.     

Explicit consideration of multiple objectives in cellular manufacturing

Although many methodologies have been proposed for solving the cell-formation problem, few of them explicitly consider the existence of multiple objectives in the design process. In this article, the development of multi-objective genetic programming single-linkage cluster analysis (GP-SLCA), an evolutionary methodology for the solution of the multi-objective cell-formation problem, is described. The proposed methodology combines an existing algorithm for the solution of single-objective cell-formation problems with NSGA-II, an elitist evolutionary multi-objective optimization technique. Multi-objective GP-SLCA is able to generate automatically a set of non-dominated solutions for a given multi-objective cell-formation problem. The benefits of the proposed approach are illustrated using an example test problem taken from the literature and an industrial case study.     

Static and dynamic operator allocation problems in cellular manufacturing systems

This paper addresses the static and dynamic operator allocation problems in cellular manufacturing systems (CMS). An assembly environment is considered where each component going into the final product is manufactured in an individual cell. There are m such cells and it is required to manufacture n varieties of products where n > m . Algorithms for static and dynamic allocation of operators to the cells to balance workload and to minimize makespan are developed and tested.     

Locating cells with bottleneck machines in cellular manufacturing systems

Because of bottleneck machines, the assignment of machine-cells to locations is interrelated with the machines' relative locations, and it makes the problem complicated to solve optimally. This paper prescribes an assignment of machine-cells to linear locations in order to minimize the inter-cell material handling cost incurred due to bottleneck machines in a cellular manufacturing system. This problem is formulated as a quadratic assignment problem (QAP). The optimal results can be obtained for a limited size of QAP. A 3-pair comparison heuristic is devised to partially overcome the dimensional problem for solving a large example. Later, an improvement heuristic called the 'bubble search' technique is developed to obtain a better solution, followed by the development of a lower bound on the QAP problem. Numerical examples are presented to illustrate the two heuristic procedures. A comparison between the optimal and heuristic solutions is also provided to evaluate the performance of the heuristics. Empirical tests conducted on two sets of data yield impressive test results.     

A network approach to cell formation in cellular manufacturing

Formation of machine cells often results in some intercellular movements between the cells. These movements cause lack of segregation among the cells. This is in conflict with the main objective of group technology which aims at independently operating cells. This paper presents a non-heuristic network approach to form manufacturing cells with minimum intercellular interactions. The machine-part matrix containing machining times is represented as a network which is subsequently partitioned by using a modified Gomory-Hu algorithm to find a minimum intercellular interaction. The modified algorithm improves the computational efficiency.     

Moveable factories: How to enable sustainable widespread manufacturing by local people in regions without manufacturing skills and infrastructure

Moveable factories enable high performance manufacturing. They carry their own power generation and are built to cover rough terrain. Hence, they have potential to enable more widespread modern manufacturing. In this paper, findings are reported from a study addressing two research questions. First, what goods should be produced by local people in regions without manufacturing skills and infrastructure? Second, how can lack of manufacturing skills and infrastructure be overcome? The study comprised literature review, semi-structured interviews, and structured questionnaire. Research participants are from Horn of Africa and from West Africa. All the goods that research participants considered to have potential for profitable production can be made with types of moveable factories that are available. Lack of local skills can be overcome through application of task design using proven techniques. In addition, techniques for designing capable production processes are applicable to moveable production. Established techniques for optimizing mix of production facilities, locations, and routes are also applicable. The robust mobility of moveable factories, and application of proven techniques, reduces the need for manufacturing infrastructure. Moveable factories are relevant to literature and debate concerning re-shoring/on-shoring/right-shoring/best-shoring manufacturing, sustainable manufacturing, advanced manufacturing, and distributed manufacturing. The relevance of moveable factories to these topics is analysed in terms of Resource-Based Theory, Knowledge-Based View, and Transaction Cost Economics.     

A similarity coefficient measure and machine-parts grouping in cellular manufacturing systems

For more than three decades, similarity coefficient measures one of the important tools for solving group technology problems have gained the attention of the research community in cellular manufacturing systems. A new similarity coefficient measure that uses a set of important characteristic properties for grouping is developed here for use as an intermediate tool to form cohesive cells. A mathematical model that uses this similarity coefficient for optimally solving the cell-formation problems in cellular manufacturing is developed. A heuristic procedure that improves the optimal methodology in term of solution capability of the large instances is devised for an efficient solution. Both the optimal methodology and the heuristic are applied to some well-known problems from literature to compare the grouping efficiencies. The similarity coefficient and the solution methodologies developed are able to solve the cell formation problems efficiently.     

A correlated storage location assignment problem in a single-block-multi-aisles warehouse considering BOM information

This paper deals with a correlated storage location assignment problem by considering the production bill of material (BOM) information. Due to the large number of parts in a BOM, the picking capacity constraint is considered. A mathematical model is formulated and a multi-stage heuristic is proposed. The heuristic relaxes the close interrelationships within the original problem through an improvement algorithm and an iterated approach to incorporate the effect of BOM splitting. In order to evaluate the performance of the heuristic, numerical experimentation is conducted in a single-block-multi-aisles warehouse, by using a randomly generated data set.     

Machine cell formation for production management in cellular manufacturing systems

The formation of machine-part families is an important task in the design of cellular manufacturing systems. Manufacturing cell grouping has the effect of reducing material handing cost and work in process. Among the many methods utilized in machine cells formation, the similarity coefficient method is most widely used. Production sequence and product volumes, if incorporated properly in determining the machine cells, can enhance the quality of solutions and reduce the number of intercellular movements. Measures for cell formation based on operations sequence utilizing ordinal production data are few and have many limitations, such as counting the number of the trips for each individual part instead of counting the weights of the batches. A new ordinal production data similarity coefficient based on the sequence of operations and the batch size of the parts is introduced. Furthermore, a new clustering algorithm for machine cell formation is proposed. The new similarity measure showed more sensitivity to the intercellular movements and the clustering algorithm showed better machine grouping.     

A comparative study of cell formation in cellular manufacturing systems

This paper analyses and evaluates six of the promising cell formation techniques by comparing and contrasting them in relation to the scores of efficiency indices of the exceptional elements and inner-cell densities, work-load balance, and under-utilizations in different scenarios. Accordingly, all six are more or less altered with proper extensions to realize a broader capability. Effectiveness of the suggested efficiency measures in the evaluation is also illustrated. Each technique seems to have a favourite operating area of its own considering a variety of factors.