An integrated model for production planning and cell formation in cellular manufacturing systems

Cellular manufacturing (CM) is a production approach directed towards reducing costs, as well as increasing system's flexibility in today's small-to-medium lot production environment. Many structural and operational issues should be considered for a successful CM design and implementation such as cell formation (CF), production planning, and facility layout. Most researchers have addressed these issues sequentially or independently, instead of jointly optimizing a combination of these issues. In order to attain better results to ensure that the system will be capable of remaining efficient in unknown future situations, these issues should be addressed simultaneously. In this paper, a mathematical model is developed using an integrated approach for production planning and cell formation problems in a CM. A set of numerical examples are provided from existing the literature in order to test and illustrate the proposed model. In order to evaluate and verify the performance of the proposed model, it is compared with a well-known cell formation methods (rank order clustering and direct clustering analysis), using group capability index (GCI) measure. The results and comparisons indicate that the proposed model has a significantly higher and satisfactory performance and it is reliable for the design and the analysis of CM systems

An improvement of a cellular manufacturing system design using simulation analysis

Cell Formation (CF) problem involves grouping the parts into part families and machines into manufacturing cells, so that parts with similar processing requirements are manufactured within the same cell. Many researches have suggested methods for CF. Few of these methods; have addressed the possible existence of exceptional elements (EE) in the solution and the effect of correspondent intercellular movement, which cause lack of segregation among the cells. This paper presents a simulation-based methodology, which takes into consideration the stochastic aspect in the cellular manufacturing (CM) system, to create better cell configurations. An initial solution is developed using any of the numerous CF procedures. The objective of the proposed method which provides performances ratings and cost-effective consist in determine how best to deal with the remaining EE. It considers and compares two strategies (1) permitting intercellular transfer and (2) exceptional machine duplication. The process is demonstrated with a numerical exampleCell Formation; Exceptional Elements; Simulation; Alternative costs; Improvement

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure

Towards a lean model for production management of refurbishment projects, VTT Technology: 94

This is the Stage 3 Report for the ApRemodel project, which aims at improving processes for multi-occupancy retrofit by generating a lean model for project delivery. In this respect, a process-driven approach has been adopted to investigate what can be done to improve the way that retrofits projects are delivered. An initial literature review, focused on the management of refurbishment works, revealed that the research on this matter is scarce. There are plenty of studies related to the broad refurbishment area, however only a small number refer to the way that those construction projects are delivered. According to the literature, construction organisations have predominantly used traditional methods for managing the production of refurbishment projects. The problem is that those tools and techniques are not often appropriate to cope with the complex characteristics inherent to construction projects, especially in the case of refurbishments. Moreover, they have often not been based on a clear theoretical foundation. As a result, numerous types of waste have been identified in refurbishment projects such as waiting time, disruptions in performing tasks on site, rework, among others. This has led to unsatisfactory project performance in terms of low productivity, project delays, and cost overrun. The first step towards better production management in refurbishment projects is recognising the complexity of the sector in order to adopt the correct approach to cope with this specific scenario. In this respect, lean construction is identified as an appropriate way to deal with the complexity and uncertainty inherent in refurbishment projects, given that this management philosophy fully integrates the conversion, flow, and value views. This document builds on the findings from the literature review as well as evidence from case studies. Managerial practices based on lean construction principles have presented successful results in the management of complex projects. Case studies available in the literature report the feasibility and usefulness of this theoretical foundation. Moreover, the evidence from these studies show considerable potential for improving the management of refurbishment works. A list of methods, tools, and techniques are identified. This report may be used by construction refurbishment organisations and housing associations as a starting point for improving the efficiency in managing production of refurbishment projects. To this end, partnerships between industry and academia are strongly recommended. 4 Although the usefulness of lean principles in complex projects is already proved, further work is needed to check what practices are best for the respective refurbishment context, as well as identifying enablers and barriers for practical adoption. Furthermore, additional studies would be also necessary to better understand the extent to which the implementation of lean philosophy might influence performance of refurbishment projects. This report should be seen as work in progress with much more to learn, as detailed research work around the sustainable retrofit process in a lean way is further developed

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