Cell Production System Design: A Literature Review

Purpose In a cell production system, a number of machines that differ in function are housed in the same cell. The task of these cells is to complete operations on similar parts that are in the same group. Determining the family of machine parts and cells is one of the major design problems of production cells. Cell production system design methods include clustering, graph theory, artificial intelligence, meta-heuristic, simulation, mathematical programming. This article discusses the operation of methods and research in the field of cell production system design. Methodology: To examine these methods, from 187 articles published in this field by authoritative scientific sources, based on the year of publication and the number of restrictions considered and close to reality, which are searched using the keywords of these restrictions and among them articles Various aspects of production and design problems, such as considering machine costs and cell size and process routing, have been selected simultaneously. Findings: Finally, the distribution diagram of the use of these methods and the limitations considered by their researchers, shows the use and efficiency of each of these methods. By examining them, more efficient and efficient design fields of this type of production system can be identified. Originality/Value: In this article, the literature on cell production system from 1972 to 2021 has been reviewed

PRABHA - A New Heuristic Approach For Machine Cell Formation Under Dynamic Production Environments

Over the past three decades, Cellular Manufacturing Systems (CMS) have attracted a lot of attention from manufacturers because of its positive impacts on analysis of batch-type production and also a wide range of potential application areas. Machine cell formation and part family creation are two important tasks of cellular manufacturing systems. Most of the current CMS design methods have been developed for a static production environment. This paper addresses the problem of machine cell formation and part family formation for a dynamic production requirement with the objective of minimizing the material handling cost, penalty for cell load variation and the machine relocation cost. The parameters considered include demand of parts in different period, routing sequences, processing time and machine capacities. In this work a new heuristic approach named PRABHA is proposed for machine cell formation and the part family formation. The computational results of the proposed heuristics approach were obtained and compared with the Genetic Algorithm approach and it was found that the proposed heuristics PRABHA outperforms the Genetic Algorithm

Tools for the design of flexible manufacturind systems

Flexibility in manufacturing systems can broaden the horizons for a company. But the means for achieving it are far more critical. This trend is created by the increase in competitiveness, growth of technology along with demand variations, more customization, and short product life cycles. But Flexible Manufacturing Systems to most of the manufacturers sounds like a synonym for automation. A real Flexible Manufacturing System is designed when every unit of the company is synchronized in such a way to respond in a harmony to any changes that come against it. Fine-tuning of each and every part of the company is essential to make the company profitably sustainable to any internal or external changes. This research aims at realizing real flexibility in the company. It aims at bringing out the bottlenecks, the issues that a company owns and tries to solve them in a feasible way so as to make the company more and more self-reliant, countering all the external and internal changes that occur during its time. A process of conducting Flexibility audit is described in thesis, which is a powerful tool when, used methodically with the FM design process (Figure 3.1), The data gathered from audit is analyzed to identify factors contributing to inflexibility and to resolve them in a feasible innovative way. This philosophy when applied continuously over a period of time can build immunity against the change shock or the adjustment time

A MULTI-OBJECTIVE GENETIC ALGORITHM APPROACH TO THE PROBABILISTIC MANUFACTURING CELL FORMATION PROBLEM

ABSTRACT Due to customised products, shorter product life-cycles, and unpredictable patterns of demand, manufacturing industries are faced with stochastic production requirements. It is unlikely that the production requirements (product mix and demand) are known exactly at the time of designing the manufacturing cell. However, a set of possible production requirements (scenarios) with certain probabilities are known at the design stage. Though a large number of research works on manufacturing cells have been reported, very few have considered random product mix constraints at the design stage. This paper presents a nonlinear mixed-integer mathematical model for the cell formation problem with the uncertainty of the product mix for a single period. The model incorporates real-life parameters like alternate routing, operation sequence, duplicate machines, uncertain product mix, uncertain product demand, varying batch size, processing time, machine capacity, and various cost factors. A solution methodology for best possible cell formation using a genetic algorithm (GA) is presented, and the computational procedure is illustrated for the case study undertaken. OPSOMMING Vanweë doelgemaakte produkte, korter produklewensiklusse en onvoorspelbare vraagpatrone, staar vervaardigingsindustrieë stochastiese produksiebehoeftes in die gesig. Dit is onwaarskynlik dat produksiebehoeftes (produkmengsel en vraag) presies bekend sal wees wanneer die vervaardigingsel ontwerp word. Desnieteenstaande sal 'n stel moontlike produksiebehoeftes (scenarios) met bepaalde waarskynlikhede tog op hierdie stadium bekend wees. Alhoewel heelwat navorsing reeds op vervaardigingselle gedoen is, is daar weinig gerapporteer waar lukraak produkmengselrandvorwaardes by die ontwerpfase oorweeg is. Hierdie artikel hou 'n nie-lineêre gemengde-heeltal-wiskundige model voor vir die selformasieprobleem met onsekerheid oor die produkmengsel in 'n enkelperiode. Die model inkorporeer werklike parameters soos alternatiewe roetes, bewerkingsvolgordes, duplikaat toerusting, onsekere produkmengsels, onsekere produkvraag, wisselende lotgroottes, prosesseertye, toerustingkapasiteit en verskeie kostefaktore. 'n Oplossingsmetodologie aan die hand van 'n genetiese algoritme vir die beste moontlike selformasie word voorgehou en die prosedure word by wyse van 'n gevallestudie geïllustreer

Performance evaluation of flexible manufacturing systems under uncertain and dynamic situations

The present era demands the efficient modelling of any manufacturing system to enable it to cope with unforeseen situations on the shop floor. One of the complex issues affecting the performance of manufacturing systems is the scheduling of part types. In this paper, the authors have attempted to overcome the impact of uncertainties such as machine breakdowns, deadlocks, etc., by inserting slack that can absorb these disruptions without affecting the other scheduled activities. The impact of the flexibilities in this scenario is also investigated. The objective functions have been formulated in such a manner that a better trade-off between the uncertainties and flexibilities can be established. Consideration of automated guided vehicles (AGVs) in this scenario helps in the loading or unloading of part types in a better manner. In the recent past, a comprehensive literature survey revealed the supremacy of random search algorithms in evaluating the performance of these types of dynamic manufacturing system. The authors have used a metaheuristic known as the quick convergence simulated annealing (QCSA) algorithm, and employed it to resolve the dynamic manufacturing scenario. The metaheuristic encompasses a Cauchy distribution function as a probability function that helps in escaping the local minima in a better manner. Various machine breakdown scenarios are generated. A ‘heuristic gap’ is measured, and it indicates the effectiveness of the performance of the proposed methodology with the varying problem complexities. Statistical validation is also carried out, which helps in authenticating the effectiveness of the proposed approach. The efficacy of the proposed approach is also compared with deterministic priority rules

A methodology for controlling the consequences of demand variability in the design of manufacturing systems

Today's unprecedented demand changes flood the global market. Staying competitive is now a matter of responding quickly and cost-effectively to variability. To address this paradigm, flexibility is a key aspect to tackle. Studies show that integrating flexibility in design of systems increases their performance by 25%, yet application procedures are still not very well established. This dissertation proposes a solution methodology for this problem. Aiming control of demand variability consequences, an integrated approach of optimization, screening, and simulation modelling has been developed. Applied to a case study in the furniture manufacturing industry, the methodology highlighted numerous opportunities of improvement in the manufacturing site. Indeed, by applying a flexible design, the overall performance goals were reached and a plan of action was initiated.The results support the proposed methodology as a viable solution for the problem addressed, nevertheless future success involves more than the pure application of this procedure, as flexibility is also a way of thinking

An Integrated Approach for the Analysis of Manufacturing System States

With advancement in the manufacturing technology and rise in the purchasing ability, demand for newer products is increasing continuously. This is forcing manufacturing companies to persistently look for new techniques to improve the productivity of a manufacturing system and ensure optimum utilization of all the elements of a manufacturing system, including facility layout. Traditional research had viewed facility layout, material handling and productivity improvement as separate activities.  Researchers depending on their area of specialization focused on either the production aspects of a company, the material handling aspects or facility layout. However, to ensure productivity, this study proposes a new theory to analyze the current state of the system with an integrated approach of production system and material handling system. In this study, the current state of the system is classified into three different states and a methodology is proposed to identify the current state of the system. This new theory can be used by manufacturers to identify appropriate strategies for improving productivity.  The identification of the state of the system is necessary for effective improvement of the system