Operator Assignment Decisions in a Highly Dynamic Cellular Environment

Operators are assigned to operations in labor-intensive manufacturing cells using two assignment strategies: Max-Min and Max. The major concern is to see how these two approaches impact operators’ skill levels and makespan values in a multi-period environment. The impact is discussed under chaotic environment where sudden changes in product mix with different operation times are applied, and also under non-chaotic environment where same product mix is run period after period. In this chapter, operators’ skill levels are affected by learning and forgetting rates. The Max-Min strategy improved operators’ skill levels more significantly than Max in this multi-period study; particularly in chaotic environment. This eventually led to improved makespan values under Max-Min strategy.

Petri Net Model Based Design and Control of Robotic Manufacturing Cells

The methods of modeling and control of discrete event robotic manufacturing cells using Petri nets are considered, and a methodology of decomposition and coordination is presented for hierarchical and distributed control. Based on task specification, a conceptual Petri net model is transformed into the detailed Petri net model, and then decomposed into constituent local Petri net based controller tasks. The local controllers are coordinated by the coordinator through communication between the coordinator and the controllers. Simulation and implementation of the control system for a robotic workcell are described. By the proposed method, modeling, simulation, and control of large and complex manufacturing systems can be performed consistently using Petri nets.

Genetic vs. Hybrid Algorithm in Process of Cell Formation

The cell formation problem has met with a significant amount of attention in recent years by demonstrating great potential for productivity improvements in production environment. Therefore, the researchers have been developing various methods based on similarity coefficient (SC), graph theory approaches, neural networks (NN), and others with aim to automate the whole cell formation process. This chapter focuses on presentation of hybrid algorithm (HA) and genetic algorithm that are helpful in production flow analysis to solve the cell formation problem. The evaluation of hybrid and genetic algorithms are carried out against the K-means algorithm and C-linkage algorithm that are well known from the literature. The comparison uses performance measure and the total number of exceptional elements (EEs) in the block-diagonal structure of machine-part incidence matrix using operational time as an input. The final performance results are presented in the form of graphs.

Developments in Modern Operations Management and Cellular Manufacturing

Operations management as a knowledge domain appears to be gaining position as a respected and dynamic academic discipline that is undergoing constant development. Therefore, from time to time it is sensible to monitor and analyze its developments by summarizing new features into comprehensive ideas. To support this necessity, the major publications/citations in this field and their evolving research utility over the decades are identified in this chapter. Because the goal of this book is to present the advancements in the area of operations management research, especially of advanced topics related to the layout design for cellular manufacturing, the second part of this chapter is focused on developments in cellular manufacturing approaches and methods by mapping literature sources during the last decade. Finally, the relationships between concept or/and tools in both areas that are empirically considered as consequences or coincidences are identified.

Multi-Modal Assembly-Support System for Cellular Manufacturing

Cellular manufacturing meets the diversified production and quantity requirements flexibly. However, its efficiency mainly depends on the operators’ working performance. In order to improve its efficiency, an effective assembly-support system should be developed to assist operators during the assembly process. In this chapter, a multi-modal assembly-support system (MASS) was proposed, which aims to support operators from both information and physical aspects. To protect operators in MASS system, five main safety designs as both hardware and control levels were also discussed. With the information and physical support from the MASS system, the assembly complexity and burden to the assembly operators are reduced. To evaluate the effect of MASS, a group of operators were required to execute a cable harness task. From the experimental results, it can be concluded that by using this system, the operators’ assembly performance is improved and their mental work load is reduced. Consequently the efficiency of the cellular manufacturing is improved.

Alternative Heuristic Algorithm for Flow Shop Scheduling Problem

In this chapter an alternative heuristic algorithm is proposed that is assumed for a deterministic flow shop scheduling problem. The algorithm is addressed to an m-machine and n-job permutation flow shop scheduling problem for the objective of minimizing the make-span when idle time is allowed on machines. This chapter is composed in a way that the different scheduling approaches to solve flow shop scheduling problems are benchmarked. In order to compare the proposed algorithm against the benchmarked, selected heuristic techniques and genetic algorithm have been used. In realistic situation, the proposed algorithm can be used as it is without any modification and come out with acceptable results.

Production Planning Models using Max-Plus Algebra

The chapter presents a novel building block approach to developing models of manufacturing systems. The approach is based on max-plus algebra. Within this algebra, manufacturing schedules are modeled as a set of coupled linear equations. These equations are solved to find performance metrics such as the make span. The chapter develops a generic modeling block with three inputs and three outputs. It is shown that this structure can model any manufacturing system. It is also shown that the structure is hierarchical, that is, a set of blocks can be reduced to a single block with the same three inputs and three output structure. Basic building blocks, like machining operations, assembly, and buffering are derived. Job shop, flow shop, and cellular system applications are given. Extensions of the theory to buffer allocation and stochastic systems are also outlined. Finally, several numerical examples are given throughout the development of the theory.

Similarity-Based Cluster Analysis for the Cell Formation Problem

This chapter illustrates the cell formation problem (CFP) supported by similarity based methods. In particular, problem oriented indices are based on several factors which play an important role in the determination of the value of similarity between two generic machines, e.g. the number of machines visited by each part, the sequence of manufacturing operations, the production quantity for each part, et cetera. A numerical example illustrates the basic steps for the implementation of an effective hierarchical procedure of clustering machines into manufacturing cells and parts/products into families of parts. Literature presents many indices, but a few significant case studies and instances not useful to properly compare them and support the best choice given an operating context, i.e. a specific production problem. As a consequence the authors illustrate an experimental analysis conducted on a literature problem oriented instance to compare the performance of different problem settings and define best practices and guidelines for professional and practitioners.

Performance Comparison of Cellular Manufacturing Configurations in Different Demand Profiles

Cellular manufacturing systems (CMSs) are an effective response in the economic environment characterized by high variability of market. The aim of this chapter is to compare different configurations of cellular models through the main performance. These configurations are fractal CMS (defined FCMS) and cellular systems with remainder cells (defined RCMS), compared to classical CMS used as a benchmark. FCMSs consist of a cellular system characterized by identical cells each capable of producing all types of parts. RCMSs consist of a classical CMS with an additional cell (remainder cell) that in specific conditions is able to perform all the technological operations. A simulation environment based on Rockwell ARENA® has been developed to compare different configurations assuming a constant mix of demand and different congestion levels. The simulation results show that RCMSs can be a competitive alternative to traditional cells developing opportune methodologies to control the loading of the cells.

Lean Thinking Based Investment Planning at Design Stage of Cellular/Hybrid Manufacturing Systems

This chapter focuses on providing a methodology for lean thinking based investment planning from the perspective of cellular or hybrid manufacturing systems. The chapter has been divided into three parts. First part provides a general explanation of why lean thinking is so beneficial for managing manufacturing processes and obtaining sustained improvement. This part then moves to the aim of cell formation, and then uses value stream mapping to map current state for visualizing material-information flow and to design a desired future state for examining economic aspects of new machine investment decisions aligned with lean manufacturing principles. The purpose of second part is to explore axiomatic design approach; it provides an overall view of what to do. The third part presents the actual use of the methodology with implementation of hybrid system at a furniture factory; it helps to see application results of this methodology as part of a lean manufacturing program.