In today’s environment of escalating competition, companies are adapting their management and production strategies, and product diversity is rapidly increasing. Companies require cellular manufacturing systems to produce products with high diversity in a short amount of time, ensuring the desired quality and meeting customer expectations. Cellular manufacturing systems, which have a more flexible structure compared to traditional production systems, are a good and effective solution for managers. Cellular manufacturing is an approach that aims to produce products with varying diversity in the shortest possible time and at the lowest cost, targeting an increase in efficiency. In this study, a cell manufacturing system proposal is made and cell formation is carried out to increase efficiency and effectiveness in a company that manufactures industrial refrigeration cabinets. A productivity-based 0-1 integer mathematical programming model is prepared that facilitates the simultaneous grouping of part and machine families in cell formation. In addition to the intracellular and intercellular transportation costs found in productivity-based models in the literature, labor costs, maintenance costs, the depreciation costs of the machines used in the cells, and the waiting costs of the machines are also added to the prepared model. The model is solved with the help of the GAMS 23.5.1 software package, creating part families and machine groups. Group efficiency values are measured, and the current and proposed situations are compared.

This paper presents a review of clustering and mathematical programming methods and their impacts on cell forming (CF) and scheduling problems. In-depth analysis is carried out by reviewing 105 dominant research papers from 1972 to 2017 available in the literature. Advantages, limitations and drawbacks of 11 clustering methods in addition to 8 meta-heuristics are also discussed. The domains of studied methods include cell forming, material transferring, voids, exceptional elements, bottleneck machines and uncertain product demands. Since most of the studied models are NP-hard, in each section of this research, a deep research on heuristics and metaheuristics beside the exact methods are provided. Outcomes of this work could determine some existing gaps in the knowledge base and provide directives for objectives of this research as well as future research which would help in clarifying many related questions in cellular manufacturing systems (CMS).

Cell formation and layout design are two important steps for the implementation of the production systems. The existing models majorly have focused on the cell formation issue and the layout design of machines, but have paid little attention to the placement of cells in dynamic environment. In addition, in most of the available papers, binary variables have been used for cell formation, and other information such as volume of production, operation sequences and production costs have played unimportant roles in the structure of the existing models. In this paper, a nonlinear program-ming model under potentially dynamic conditions is proposed which minimizes the cost associated with the difference between the estimated demands from its expected value. The other purpose of the proposed model includes minimization of the total costs of inter/intra cellular movements of elements (forward and backward movements), the existence of exceptional elements, intercellular displacement of machines and cellular reconfiguration and operational costs and constant cost of machineries. The problem is solved via GAMS and a Genetic Algorithm (GA) is employed to solve the large sized problems and the results are analyzed.

This paper presents a review of human resource planning methods, related techniques, and their effects on cellular manufacturing systems (CMS). In-depth analysis has been conducted through a review of 43 dominant research papers available in the literature. The advantages, limitations, and drawbacks of material transferring methods have been discussed as well. The domains of the examined studies include some of the important problems in staff planning, such as worker assigning, hiring and firing, optimum number of workers, skilled workers, cross-functional experts, worker satisfaction and outsourcing. The results of this study can fill research gaps and clarify many related questions in CMS problems.