Statistical process control and Shewhart control charts are used by organizations to aid in process understanding, assessing process stability, and identifying changes to improve the quality of the product. Shewhart control charts only considered uncertainty caused by randomness while in practice, uncertainty caused by vagueness, ambiguity, and/or incomplete information are also observed. In this article, fuzzy X¯ − S control charts which handle both kinds of uncertainty simultaneously are developed using fuzzy random variables. For this purpose, the unbiased estimation of standard deviation for a triangular fuzzy random variable is introduced and utilized to construct the fuzzy X¯ − S control charts. Then, a detailed average run length study is performed to evaluate the decisions regarding sample size and accepted outof-control level ( ). A comparison study is performed to verify the proposed technique by comparing its performance based on average run length with previous technique in the literature. The result shows that the proposed technique could improve the detection of abnormal shift in process mean 0.1% to 30% depending on sample size and shift. Finally, the proposed fuzzy control charts are validated through a case study of noodle production in food industry.

Cellular manufacturing system is a submission of group technology wherein are different machines or processes have been combined into cells, each of which is devoted to the fabrication of a part, product family, or limited group of families. Cell formation is necessary for implementation of cellular manufacturing. Many of methods exist for cell formation problem solving. Some of these methods are applying in traditional cell design, in fixed routines and others are applying in dynamic cells environment. In this review article, critical assessment of various metaheuristic techniques which utilized in cell formation problem solving is made through extensive literature review. Various existing models for cell formation are argued consequently and directions for future work are presented.

a b s t r a c t A cellular manufacturing system (CMS) is considered an efficient production strategy for batch type production. A CMS relies on the principle of grouping machines into machine cells and grouping parts into part families on the basis of pertinent similarity measures. The bacteria foraging algorithm (BFA) is a newly developed computation technique extracted from the social foraging behavior of Escherichia coli (E. coli) bacteria. Ever since Kevin M. Passino invented the BFA, one of the main challenges has been employment of the algorithm to problem areas other than those for which the algorithm was proposed. This research work studies the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem considering the operation sequence. In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. In this paper, an attempt is made to solve the CF problem, while taking into consideration the number of voids in the cells and the number of inter-cell travels based on operational sequences of the parts visited by the machines. The BFA is suggested to create machine cells and part families. The performance of the proposed algorithm is compared with that of a number of algorithms that are most commonly used and reported in the corresponding scientific literature, such as the CASE clustering algorithm for sequence data, the ACCORD bicriterion clustering algorithm and modified ART1, and using a defined performance measure known as group technology efficiency and bond efficiency. The results show better performance of the proposed algorithm.

Facility layout design problems are a group of problems that involve the partitioning of a region into work centers or departments to minimize the costs associated with interactions between the work centers and departments. In cellular manufacturing systems, facility layout problem aims to find the most efficient arrangement of facilities within the machine cells and the layout of machine-cells within the workshop. In this paper, an algorithm for solving layout design has been proposed that arranges the machines within machine cells, and cells in the shop-floor in such a way that minimizes the total material handling cost. To validate the developed algorithm, the results obtained by the algorithm are compared to the results of an exhaustive search. Comparison of results shows the validity of the proposed algorithm.

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