Performance Of Cellular Manufacturing Systems Research Articles

Simultaneous consideration of time and cost impacts of machine failures on cellular manufacturing systems

Cellular manufacturing systems (CMS) are essential for achieving efficient production processes, and their success relies on effective cell formation and layout design. This research paper presents a novel nonlinear mathematical programming model that employs the rectilinear distance notion to define the layout within a continuous space. The proposed model incorporates the stochastic nature of machine failures, considering the unreliability with the inclusion of a stochastic time between failures. With a bi-objective approach, the model aims to minimize inter and intra-cell movements of parts, as well as the associated costs related to exceptional elements (EEs), cell reconfigurations, and machine failures. To optimize the proposed model, several multi-objective meta-heuristic algorithms, including the multi-objective particle swarm optimization (MOPSO), multi-objective taboo search (MOTS), and non-dominated sorting genetic algorithm (NSGA-II), are introduced. The effectiveness of these algorithms is validated through numerical instances and a real case study. The results indicate that the MOPSO algorithm exhibits superior performance in optimizing various multi-objective criteria. The presented mathematical model and algorithms provide valuable tools for manufacturers to optimize their CMS, resulting in reduced costs, enhanced production efficiency, and increased competitiveness. By considering the simultaneous effects of time and cost associated with machine failures, this research offers practical insights and solutions for improving the performance of cellular manufacturing systems.

A Multi-Criteria Assessment of Manufacturing Cell Performance Using the AHP Method

Research of manufacturing cell design problems is still pertinent today, because new manufacturing strategies, such as mass customization, call for further improvement of the fundamental performance of cellular manufacturing systems. The main scope of this article is to find the optimal cell design(s) from alternative design(s) by multi-criteria evaluation. For this purpose, alternative design solutions are mutually compared by using the selected performance criteria, namely operational complexity, production line balancing rate, and makespan. Then, multi-criteria decision analysis based on the analytic hierarchy process method is used to show that two more-cell solutions better satisfy the determined criteria of manufacturing cell design performance than three less-cell solutions. The novelty of this research approach refers to the use of the modification of Saaty’s scale for the comparison of alternatives in pairs based on the objective assessment of the designs. Its benefit lies in the exactly enumerated values of the selected criteria, according to which the points from the mentioned scale are assigned to the alternatives.

A Simulation Analysis of The Effects of System Parameters and Operating Strategies on The Performance of Cellular Manufacturing Systems.(Dept.M)

A Simulation Analysis of The Effects of System Parameters and Operating Strategies on The Performance of Cellular Manufacturing Systems.(Dept.M)

An optimisation approach for simulation operator allocation and job dispatching rule in a cellular manufacturing system

The purpose of this article is to present an approach based on simulation optimisation for improving the performance of cellular manufacturing systems through optimising operator allocation and job dispatching rules in each cell. In this study, we have considered stochastic parameters, machines' breakdown and multiple products in order to consider the problem as close as possible to real world situation. The presented approach is composed of Taguchi design of experiments, discrete event simulation, artificial neural networks, and data envelopment analysis. After determining the optimum scenario, it is compared to the present condition of the case and the improvements are determined. In order to evaluate the performance of the presented approach, lathing factory which uses cellular manufacturing system is considered as the case study.

An Optimization Approach for Simulation Operator Allocation and Job Dispatching Rule in a Cellular Manufacturing System

The purpose of this article is to present an approach based on simulation optimisation for improving the performance of cellular manufacturing systems through optimising operator allocation and job...

NSGA Based Algorithm for Energy Efficient Scheduling in Cellular Manufacturing

Energy efficient scheduling is assuming significance due to focus on sustainable manufacturing practices as well as environmental impact. Many researchers have proposed algorithms/methodologies for scheduling in manufacturing environment including cellular manufacturing. However, very few studies have been reported in the area of cellular manufacturing with a focus on minimizing makespan, flowtime and energy consumption. In this study, we propose NSGA based algorithm for minimizing makespan, flowtime as well as energy consumption by the manufacturing resources in the context of cellular manufacturing system. Based on our earlier study, it is noted that the operational performance of cellular manufacturing systems depends on the percentage of missing operations and scheduling approach (such as dispatching rules) used. Our preliminary studies show that there is a significant potential for improving the schedule of operations by considering energy consumption. From the limited experimental results, it is noted that the flow time, makespan and idle time was decreased in few cases with the combined objective. We propose to conduct a detailed study on the test problems in flowshop configuration and cellular manufacturing context with the objective of minimization of flow time, makespan, idle time and energy consumption.

セル生産システムの主要成功要因、組織成熟度、推進成果の関連性に関する研究

セル生産システムの主要成功要因、組織成熟度、推進成果の関連性に関する研究

Developing a logical model for cellular manufacturing systems by theory of constraints thinking process approach

Performance of cellular manufacturing systems has been rigorously investigated during the last two decades. Many of these studies are quantitative and involve precise modelling. The purpose of this paper is to determine critical factors in cellular manufacturing system (CMS) and to identify relationships between different factors of CMS via systematic approach of the theory of constraint thinking process. For this purpose, potential undesirable effects and critical factors of CMS have been identified through a brainstorming session with experts. Then, factors are analysed using thinking process by examining casual relationships, and some strategies have been suggested based on the critical factors. Findings show that knowledge of managers, management information system, performance evaluation, market demands, work-in-process inventory, number of cells, assigning of workers to cells, and identification of part families are recognised as the critical factors in strategic decision making. The proposed factors and the relationships have been validated by 68 experts using a binomial test.

Impact of the use-based maintenance policy on the performance of cellular manufacturing systems

In this paper, a multi-objective integer programming approach is developed to investigate the impact of the use-based preventive maintenance (UPM) policy on the performance of the cellular manufacturing system (CMS). Under the UPM policy a maintenance schedule is established which provides for the performance of preventive maintenance (PM) only after a predetermined number of operating hours of machine use. This research indicates how PM and failure repair (FR) actions affect the effective availability of the machines and accordingly the machine and inter/intra-cell material handling costs under the UPM policy. The objective is to minimise the machine cost, inter- and intra-cell material handling and PM/FR costs. The proposed model is solved by an interactive fuzzy programming (IFP) approach to determine the best compromise solution from the decision maker point of view. IFP assumes that each objective function has a fuzzy goal and focuses on minimising the worst upper bound to obtain an efficient solution which is close to the best lower bound of each objective function. Compromise solutions are prioritised by two efficiency criteria, i.e. grouping efficiency and system availability. The performance of the proposed model is verified by a comprehensive numerical example.

Scheduling in cellular manufacturing systems: an heuristic approach

Adopting cellular manufacturing, which enables achieving the goals of just-in-time (JIT) philosophy, has benefited many world-class organizations. Many approaches have been developed for the design of cellular manufacturing systems (CMS). Scheduling of parts and part families in CMS is an important issue. In this study scheduling in flowline-based CMS is addressed by considering varying degrees of missing operations for parts in a cell. A simulated annealing (SA)-based algorithm has been developed for scheduling of parts within a cell for the objective of minimization of weighted sum of makespan, flowtime and idletime. The algorithm makes use of a pool of nine popularly used dispatching rules in scheduling literature. The performance of the proposed algorithm is evaluated using an alternative algorithm with three dispatching rules, and has been proposed and evaluated for minimization of weighted sum of makespan, flowtime and idletime. The proposed algorithm was also evaluated considering two benchmark algorithms, NEH heuristic for minimization of makespan and RC heuristic for minimization of flowtime. From the limited experimental results, it is found that the performance of the proposed algorithm with a larger pool of dispatching rules performs better than the three algorithms tested. Based on the results of the study, it is also found that the operational performance of CMS depends on the percentage of missing operations and scheduling approach (such as dispatching rules) used.

Evolutionary approach for solving cell-formation problem in cell manufacturing

New environmental characteristics and requirements have challenged manufacturing enterprises to improve the efficiency and productivity of their production activities. Cellular manufacturing (CM) as one of the solutions to this problem, as implementation of Group technology (GT), was proposed. Performance of cellular manufacturing systems depends heavily on the cell structure. In this paper we present and evaluate a novel approach for solving the cell-formation problem based on implementation of a GA, called modified genetic algorithm (MGA). Implementation of the GA in here presented simulation model is based on Emergent Synthesis idea, of top-down problem decomposition and emerging solution from bottom-up feedback.

Evaluation of dispatching rules for cellular manufacturing

In this paper, the effects of various dispatching rules on the operation and performance of cellular manufacturing systems (CMS) are evaluated. When the study of a CMS considers the automated material handling, it is crucial to reduce the gridlock probability (i.e., the probability of an unsuccessful load transfer attempt occurring in the interface point between the intercell and intracell handling system). Preventing an unsuccessful load transfer is critical for the operation of the entire system as a blockage between the automated guided vehicle (AGV) and the overloaded cell results in a total system shutdown. The gridlock probability is influenced by the dispatching rule used to schedule the load transfers in the system. Therefore, in order to reduce this probability it is necessary to use a dispatching rule that will decrease the number of waiting loads in the transfer spurs. The main objective of the paper presented herein is to identify a dispatching rule that maintains the system operational at all times. A group of dispatching rules, including the first come first served (FCFS), shortest imminent operation (SI), longest imminent operation (LI), most remaining operations (MRO), shortest processing time (SPT), shortest remaining process time (SR), and a newly developed rule proposed by the authors, loads with the minimum number of processing first (MNP), are tested and evaluated with respect to whether the capacity of the transfer spurs of the cells is exceeded. This paper presents a simulation model of a cellular manufacturing system, which is used to further explore the effects of the dispatching rules on the system performance. The results show superior performance of the newly proposed MNP rule.

Improving the performance of cellular manufacturing by a dynamic part assignment approach

In this paper, a simple dynamic part assignment (DPA) procedure is introduced and its effects on the performance of cellular manufacturing systems is evaluated. In this procedure rerouting of parts among machine cells is allowed for better machine utilization. Three data sets are used to compare the performance of manufacturing systems under job shop and cellular manufacturing when DPA is employed. The results of simulation runs indicate that the proposed DPA method improves the performance of cellular manufacturing significantly by reducing the congestion in machine cells with long waiting lines.

Machine sharing and performance of cellular manufacturing systems

In this paper, we examine the impact of machine sharing on performance of traditional cellular manufacturing systems. We present an analytical model for evaluating the desirability of sharing machines of the same type among two or more cells. The effect of machine sharing on several performance measures, such as machine utilizations, cell production rates, and part flow times, is studied under varying conditions of system loading, setup time, and batch sizes. Conditions under which machine sharing may be of value and the operating requirements necessary for realizing this value are identified. A model for trading off costs and benefits of machine sharing and determining optimal levels of machine sharing is also presented.

Manufacturing cell formation under random product demand

The performance of cellular manufacturing systems is intrinsically sensitive to demand variations and machine breakdowns. A cell formation methodology that addresses, during the shop design stage, system robustness with respect to product demand variation is proposed. The system resources are aggregated into cells in a manner that minimizes the expected inter-cell material handling cost. The statistical characteristics of the independent demand and the capacity of the system resources are explicitly considered. In the first step of the proposed approach the expected value of the feasible production volumes, which respect resource capacities, are determined. Subsequently, the shop partition that results in near optimal inter-cell part traffic is found. The applicability of the proposed approach is illustrated through a comprehensive example.

Performance analysis of machine cell configurations using simulation

The objective of this research is to develop a generalized model that can analyze the performance of any cellular manufacturing system under various combinations of dispatching and loading policies. Early stages of the research along this line before generalization of the model is presented in this paper. A menu-driven SIMAN based simulation model is developed to analyze the performance of a particular cellular manufacturing system in terms of machine utilization, tool utilization, transporter (AGV) utilization, part waiting time, etc.