The evolution of cell formation problem methodologies based on recent studies (1997-2008): review and directions for future research

This paper presents a literature review of the cell formation (CF) problem concentrating on formulations proposed in the last decade. It refers to a number of solution approaches that have been employed for CF such as mathematical programming, heuristic and metaheuristic methodologies and artificial intelligence strategies. A comparison and evaluation of all methodologies is attempted and some shortcomings are highlighted. Finally, suggestions for future research are proposed useful for CF researchers

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

Bi-Level Mathematical Modelling and Heuristics for Cellular Manufacturing Facility Layout Problem

In this thesis, a bi-level mixed-integer non-linear programming continuous model has been, developed for both intra-cell and inter-cell layout design sequentially. Facilities are assumed unequal sizes, and operation sequences and part demands are considered. The model includes overlap elimination, aisle, and block constraints. Since the model is nonlinear, the model has been linearized and solved exact. However, the facility layout problem is NP-hard; hence, novel heuristics and a meta-heuristic have been designed and implemented to solve the problem in a similar manner- both at intra- and inter-cellular levels. A real case study from the metal cutting inserts industry has been used where multiple families of inserts have been formed each with its distinguished master plan. C++ has been used for implementation of the algorithms. For mathematical programming, the model is being solved by the Xpress optimization tool using a branch-and-bound method to illustrate the performance of the model

Algorithms and Methods for Designing and Scheduling Smart Manufacturing Systems

This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book

Improved Physical Design for Manufacturing Awareness and Advanced VLSI

Increasing challenges arise with each new semiconductor technology node, especially in advanced nodes, where the industry tries to extract every ounce of benefit as it approaches the limits of physics, through manufacturing-aware design technology co-optimization and design-based equivalent scaling. The increasing complexity of design and process technologies, and ever-more complex design rules, also become hurdles for academic researchers, separating academic researchers from the most up-to-date technical issues.This thesis presents innovative methodologies and optimizations to address the above challenges. There are three directions in this thesis: (i) manufacturing-aware design technology co-optimization; (ii) advanced node design-based equivalent scaling; and (iii) an open source academic detailed routing flow.To realize manufacturing-aware design technology co-optimization, this thesis presents two works: (i) a multi-row detailed placement optimization for neighbor diffusion effect mitigation between neighboring standard cells; and (ii) a post-routing optimization to generate 2D block mask layout for dummy segment removal in self-aligned multiple patterning.To achieve advanced node design-based equivalent scaling, this thesis presents two improved physical design methodologies: (i) a post-placement flop tray generation approach for clock power reduction; and (ii) a detailed placement approach to exploit inter-row M1 routing for congestion and wirelength reduction.To address the increasing gap between academia and industry, this thesis presents two works toward an open source academic detailed routing flow: (i) a complete, robust, scalable and design ruleaware dynamic programming-based pin access analysis framework; and (ii) TritonRoute – the open source detailed router that is capable of delivering DRC-clean detailed routing solutions in advanced nodes.This thesis concludes with a summary of its contributions and open directions for future research

Group Scheduling in a Cellular Manufacturing Shop to Minimise Total Tardiness and nT: a Comparative Genetic Algorithm and Mathematical Modelling Approach

In this paper, family and job scheduling in a cellular manufacturing shop is addressed where jobs have individual due dates. The objectives are to minimise total tardiness and the number of tardy jobs. Family splitting among cells is allowed but job splitting is not. Two optimisation methods are employed in order to solve this problem, namely mathematical modelling (MM) and genetic algorithm (GA). The results showed that GA found the optimal solution for most of the problems with high frequency. Furthermore, the proposed GA is efficient compared to the MM especially for larger problems in terms of execution times. Other critical aspects of the problem such as family preemption only, impact of family splitting on common due date scenarios and dual objective scenarios are also solved. In short, the proposed comparative approach provides critical insights for the group scheduling problem in a cellular manufacturing shop with distinctive cases

Formación de celdas de manufacturas dinámicas para la toma de decisiones en el diseño de instalaciones industriales: una revisión

This paper presents a literature review with the purpose of characterizing the Dynamic Manufacturing Cell Formation Problem by means of the identification of optimization criteria, the most relevant restrictions needed for consideration and the most frequently used solution methods. Hence, an adaptation of the PRISMA statement was conducted for systematic reviews along with Snowball Methodology to select the studies to be analyzed. The document search is carried out in the Web of Science and Scopus databases, considering a time frame between 2007 and 2019. As a general result, it was found that cost minimization is the most frequently used optimization criterion and the typically considered constraints are associated with part machine operation sequence, machine breakdowns, and lot size. On the other hand, considering the highly combinatorial nature of the optimization problems reviewed, it was found that metaheuristics are the most used solution method, and genetic algorithms as well as simulated annealing are the most frequently implemented. Finally, three research trends are determined: incorporation of two or more optimization criteria in a mathematical formulation, development and implementation of hybrid metaheuristic algorithms, and comparison of performance of the existing solution methods based on reference problems or real industrial applications.Este artículo presenta una revisión de literatura con el fin de caracterizar el Problema de Formación de Celdas de Manufactura Dinámicas, realizando la identificación de los criterios de optimización, las principales restricciones consideradas y los métodos de solución más usados. Para ello, se condujo una adaptación de la declaración PRISMA para revisiones sistemáticas, en conjunto con una metodología bola de nieve para la selección de los estudios a analizar; la búsqueda de documentos se realiza en las bases de datos Web of Science y Scopus, considerando una ventana de tiempo entre 2007 y 2019. Como resultados generales, se encuentra que la minimización de costos es el criterio de optimización utilizado con mayor frecuencia y que las restricciones usualmente consideradas están asociadas a la secuencia de operaciones, averías de máquinas, y variación del tamaño de lote de procesamiento. De otra parte, considerando la naturaleza altamente combinatoria de los problemas de optimización revisados, se encuentra que los métodos de solución metaheurísticos utilizados en mayor medida son algoritmos genéticos, y recocido simulado. Finalmente, se determinan tres tendencias de investigación primero, la incorporación de dos o más criterios de optimización en una formulación matemática; segundo, el desarrollo e implementación de algoritmos metaheurísticos híbridos y; tercero, la evaluación de los métodos de solución existentes a partir de problemas de referencia o aplicaciones industriales reales

Designing Stochastic Cell Formation Problem Using Queuing Theory

This paper presents a new nonlinear mathematical model to solve a cell formation problem which assumes that processing time and inter-arrival time of parts are random variables. In this research, cells are defined as a queue system which will be optimized via queuing theory. In this queue system, each machine is assumed as a server and each part as a customer. The grouping of machines and parts are optimized based on the mean waiting time. For solving exactly, the proposed model is linearized. Since the cell formation problem is NP-Hard, two algorithms based on genetic and modified particle swarm optimization (MPSO) algorithms are developed to solve the problem. For generating of initial solutions in these algorithms, a new heuristic method is developed, which always creates feasible solutions. Also, full factorial and Taguchi methods are used to set the crucial parameters in the solutions procedures. Numerical experiments are used to evaluate the performance of the proposed algorithms. The results of the study show that the proposed algorithms are capable of generating better quality solutions in much less time. Finally, a statistical method is used which confirmed that the MPSO algorithm generates higher quality solutions in comparison with the genetic algorithm (GA)