Approach For Cell Formation Research Articles

User-Centric Secure Cell Formation for Visible Light Networks With Statistical Delay Guarantees

In next-generation wireless networks, providing secure transmission and delay guarantees are two critical goals. However, either of them requires a concession on the transmission rate. In this article, we consider a visible light network consisting of multiple access points and multiple users. Our first objective is to mathematically evaluate the achievable rate under constraints on delay and security. The second objective is to provide a cell formation with customized statistical delay and security guarantees for each user. First, we propose a user-centric design called secure cell formation, in which artificial noise is considered, and flexible user scheduling is determined. Then, based on the effective capacity theory, we derive the statistical-delay-constrained secrecy rate and formulate the cell formation problem as a stochastic optimization problem (OP). Further, based on the Lyapunov optimization theory, we transform the stochastic OP into a series of evolutionary per-slot drift-plus-penalty OPs. Finally, a modified particle swarm optimization algorithm and an interference graph-based user-centric scheduling algorithm are proposed to solve the OPs. We obtain a dynamic independent set of scheduled users as well as secure cell formation parameters. Simulation results show that the proposed algorithm can achieve a better delay-constrained secrecy rate than the existing cell formation approaches.

Cell Formation Based on New Similarity Coefficient with Operation Sequence and Alternative Routing

Cell formation is to construct machine cells and part families and then dispatch the part families to machine cells. Various cell formation approaches and algorithms have been developed over the years considering various production factors, scenarios and objectives. The results of these different approaches are evaluated based on the several parameters. Most of the studies have considered only either the operation sequence or the alternative routing. Very few of the approaches have proposed for considering both the operation sequence and the alternative routing. Here, a new method for the formation of cell and intracellular machine arrangement which is formulated by considering both the operation sequence and alternative process routings is proposed. The arrangement of machines and parts within the cell follows a specific sequence which is formed with the help of coefficient of similarity. Various parameters such as forward flow, backflow and voids in the cell formation scenarios are considered to evaluate the approach. With the help of these parameters problems from other literatures, which were solved by other methods are evaluated. So as to validate the effectiveness of our proposed approach, five eminent test problems from the previous literature are engaged and the results are compared with the existing method the results clearly display that the proposed approach which that provides superior or equal solution than the existing method.

Cell Formation Based on New Similarity Coefficient with Operation Sequence and Alternative Routing

Cell formation is to construct machine cells and part families and then dispatch the part families to machine cells. Various cell formation approaches and algorithms have been developed over the years considering various production factors, scenarios and objectives. The results of these different approaches are evaluated based on the several parameters. Most of the studies have considered only either the operation sequence or the alternative routing. Very few of the approaches have proposed for considering both the operation sequence and the alternative routing. Here, a new method for the formation of cell and intracellular machine arrangement which is formulated by considering both the operation sequence and alternative process routings is proposed. The arrangement of machines and parts within the cell follows a specific sequence which is formed with the help of coefficient of similarity. Various parameters such as forward flow, backflow and voids in the cell formation scenarios are considered to evaluate the approach. With the help of these parameters problems from other literatures, which were solved by other methods are evaluated. So as to validate the effectiveness of our proposed approach, five eminent test problems from the previous literature are engaged and the results are compared with the existing method the results clearly display that the proposed approach which that provides superior or equal solution than the existing method.

Hybrid cellular manufacturing system design with cellularisation ratio: an integrated mixed integer nonlinear programming and discrete event simulation approach

This study investigates hybrid cellular manufacturing system design where products with highly similar process routes are formed as manufacturing cells, and products with dissimilar routes are produced in a process layout. A cell similarity threshold, cellularisation ratio (C-ratio), is proposed for product assignment to cells and process layout, and integrated into a mathematical modelling-based cell formation approach. The cell formation phase is carried out with the proposed mathematical model. Several case problems are tested, and selected cases are also studied with a newly developed simulation model where manufacturing system performance is also evaluated along with the proposed hybrid cellular manufacturing design alternatives. Results indicated that considering a C-ratio during cell formation can provide higher cell similarity thus better cell formation. The increase in the coverage levels resulted in higher number of cells formed. The proposed approach can be significantly beneficial for manufacturing design decisions where product mix and process complexity are high, and for a hybrid layout that consists of cellular plus process layouts could be implemented.

A comparison of manufacturing and disassembly systems from a cellular configuration point of view

The main aim of this research is to analyze the differences between cellular manufacturing and cellular disassembly systems. While doing so, this paper makes a relevant contribution. It proposes a mathematical programming formulation for robust manufacturing and disassembly cell formation problems. A solution method based on the Tabu Search schema is adapted for both problems and will be used for the comparison analysis. The fact that the Tabu Search algorithm has been effective in different cell formation approaches gives us confidence in its reliability, and although alternative metaheuristic approaches may be developed in the future, we opted for adapting this algorithm to the problem at hand, since our first aim is to obtain data to analyze the difference in the design of both types of production environments and not to develop new approaches to the cell formation problem. A full factorial design study is proposed in order to appraise the significance of controllable factors in cellular designs. Four dependent variables were considered in the experiments: total cost, size of the cells, number of intercellular moves, and machine utilization. The issue here is to see what happens with the solutions for each production environment (manufacturing and disassembly) when varying factors, in order to analyze the differences and similarities between both.

Production-Oriented Cell Formation Methods and Performance Indicators: Taxonomic Review and Trends

Cellular manufacturing, one of the main tools of Lean Manufacturing, significantly improves material flow, which reduces the distance travelled by materials, inventory and cumulative lead times. In our study we focused on examination of the recent trends in cellular manufacturing research, and particularly the trends related to cell formation areas, objective criteria, performance measures, and development tools. The surveyed articles are organized by proposed classification scheme, and they are presented in synoptic graph diagrams. In the paper we also identify the best publication outlets for such research. Our survey on cell formation approaches identifies the major development features in cell manufacturing research area in leading journals between 2000 and 2011. Subsequently, the main findings are summarized and presented in the last part of the paper.

Growing hierarchical self-organizing map computation approach for clustering in cellular manufacturing

This article focuses on approach that provides visualization of machine–part clustering in cellular manufacturing system based on sequence of operation. We propose a novel cell formation approach, namely the growing hierarchical self-organizing map (GHSOM), for dealing with 14 benchmark problems from literature. The performance of the proposed algorithm is tested with the problem data sets and the results are compared using the group technology efficiency (GTE) and computational time with the existing traditional clustering algorithms. It is found that the proposed algorithm resulted in an increase in GTE in most of the problem data sets, and the outputs of cell formation are either superior or same as existing methods. The outputs of the experiments conducted in this research lead us to the conclusion that the GHSOM is a promising alternative cell formation algorithm owing to its adaptive architecture and the ability to expose the hierarchical structure of data.

A neuro-agglomerative approach to strategic design of a manufacturing cell

Intelligent design of cells in industrial manufacturing popularly known as cellular manufacturing systems (CMS) has attained the significant attention of academicians and researchers over the last three decades. It is an efficient production strategy for batch type of production. Over the years, various approaches have been used in cell formation and continue to attract researchers with new and improved approaches and experimentation. In this paper, a neuro-agglomerative algorithm is proposed to simplify strategic design of manufacturing cell in cellular manufacturing systems. The algorithm designed is cable of evaluating problems both in simple binary form and non-binary form considering processing time as a production factor. The performance of the proposed technique is tested on the benchmark problems and compared to popular cell formation approaches as found in the recent literature. The results support the better performance of the proposed algorithm.

A comprehensive approach to facility layout design and cell formation

Group technology (GT) and a facility layout problem share a common factor to optimize, which is the “Intercell Flow or Material Handling Flow”. Most group technology-based approaches use binary part-machine incidence matrix for cell formation. Impacts of flow volume analysis between machine pairs have not been analyzed in the design of cellular manufacturing systems. It is important to analyze the placement of machine cells for reduced material handling costs at the grouping stage itself. This paper develops a method to integrate GT philosophy with a facility layout problem using “From–Between” relationship chart as a tool. A new optimization technique with a “from–to chart” as the primary input, is used to determine the cell formation. A modified grouping efficiency measure is used to determine the efficiency of grouping. A genetic algorithm-based approach is used for machine cell placement within a layout matrix. Cells formed using the proposed approach show reduced intercell flows, high grouping efficiencies and reduced material handling costs when cells are placed in a layout grid compared to existing cell formation approaches.

A new approach for cell formation and scheduling with assembly operations and product structure

In this paper, a new formulation model for cellular manufacturing system (CMS) design problem is proposed. The proposed model of this paper considers assembly operations and product structure so that it includes the scheduling problem with the formation of manufacturing cells, simultaneously. Since the proposed model is nonlinear, a linearization method is applied to gain optimal solution when the model is solved using direct implementation of mixed integer programming. A new genetic algorithm (GA) is also proposed to solve the resulted model for large-scale problems. We examine the performance of the proposed method using the direct implementation and the proposed GA method. The results indicate that the proposed GA approach could provide efficient assembly and product structure for real-world size problems.

A Two-Stage Cell Formation Approach with Machine Performance

Cell formation which involves grouping similar parts into part families and the corresponding machines into machine cells is one of the key research issues for designing cellular manufacturing system. Functionally identical machines may vary in production performance. In the paper, processing cost is employed to differentiate the performance of machines, and a two-stage cell formation approach for manufacturing systems with multiple functionally identical machines is proposed. With this approach, parts are firstly clustered into part groups based on process similarity; secondly, machines are then assigned to part groups according to their performance to form manufacturing cells. A heuristic algorithm based on process similarity is presented for part group identification, and a mathematical model with the objective of minimizing the total processing cost is established. An example is employed to illustrate the benefit of the proposed approach and the results suggest that the proposed approach is feasible.

Configuration Flexibility in Virtual Cellular System

In today’s competitive world, producers of goods are under constant and intense pressure to quickly and continuously improve their operations by enhancing productivity, quality and responsiveness. Virtual cellular manufacturing (VCM) is being used as a philosophy with broad applicability in manufacturing sector to reduce movement of jobs, set-up times and lead times. As a result, there is a surge of interest in this area by the industry. The paper provides an integrated framework for the development of solution methods and heuristics by incorporating various flexibilities in the formation of virtual cells within job shop setup. Through an extensive review of literature in traditional manufacturing areas, a new approach for cell formation that integrates machine grouping and layout design is followed with flexibility as a main focus in this paper. The proposed framework will try to address several performance evaluation issues such as system utilization, work-in-process inventory and related flexibilities.

A new approach for formation of virtual cells

In this paper, a new approach for cell formation that integrates machine grouping and layout design, neglecting part-family formation, has been presented. The procedure includes four phases. In Phase 1, primary cells are formed by dividing operations into three ranges. Phase 2 involves redesigning of primary cells for minimisation of the number of intercell travels and to address the machine duplication problem. Phase 3 involves decomposition of individual primary cells into sub-cells. Phase 4 involves forced decomposition of sub-cells to obtain multiple cell designs. The efficacy of the methodology is demonstrated through an illustrative example.

Uncertain association rule mining algorithm for the cell formation problem in cellular manufacturing systems

Although data mining has enjoyed popularity in recent years with advances in both academia and industry, the application of data mining to cellular manufacturing, one of the most powerful management innovations in job-shop or batch-type production, is still under-utilized. Based on association rule mining, Chen initially developed a cell formation approach. One problem of such a cell formation algorithm is that various real-life production factors were ignored. In this paper we propose a new cell formation algorithm by way of uncertain association rule mining. The proposed algorithm incorporates several key production factors, such as operation sequence, production volume, batch size, alternative process routings, cell size, the number of cells, and the path coefficient of material flow. The efficacy and efficiency of the proposed algorithm were tested using several numerical problems.

A robust cell formation approach for varying product demands

In cellular manufacturing environments, manufacturing cells are generally formed based on deterministic product demands. In this paper, we consider a system configuration problem with product demands expressed in a number of probabilistic scenarios. An optimization model integrating cell formation and part allocation is developed to generate a robust system configuration to minimize machine cost and expected inter-cell material handling cost. A two-stage Tabu search based heuristic algorithm is developed to find the optimal or near optimal solutions to the NP-hard problem. Numerical examples show that this model leads to an appropriate compromise between system configuration costs and expected material handling costs to meet the varying product demands. These example problems also show that the proposed algorithm is effective and computationally efficient for small or medium size problems.

A genetic-based algorithm with the optimal partition approach for the cell formation in bi-directional linear flow layout

This paper addresses the joint problem of the cell formation and the intercell layout, in which machine cells are located along a linear flow layout. The objective is to minimize the actual intercell flow cost, instead of the typical measure that optimizes the number of intercell movements. A genetic-based algorithm with optimal partition approach is developed for solving the joint problem. In the proposed approach, the genetic operators are used to generate a pool of solutions, where the solution represents the sequence of machines in the linear layout and each sequence of machines is an individual in the population. The evaluation function, machine cells and its intercell flow cost of each solution are determined by a dynamic programming algorithm, where a sequence of machines is partitioned into several segments or cells, subject to a cell size constraint. In this sense, the genetic algorithm is enhanced with the optimization framework in the proposed approach. The computational efficiency has also been improved since the number of machine cells does not need to be specified in advance in the cell formation approaches. Numerical studies, including 14 data sets adapted from the literature, are performed to demonstrate the viability of the approach.

Configuration of cellular manufacturing systems using association rule induction

A cell-formation approach based on association rule induction is developed to find the effective configurations for cellular manufacturing systems. To gain the benefits of flexibility and efficiency, the manufacturing system is decomposed into several manageable subsystems by categorizing similar parts into part families and disparate machines into cells. It is advantageous to find the important associations among machines such that the occurrence of some machines in a machine cell will cause the occurrence of other machines in the same cell. Relationships among machines can be found from the process database by inducting association rules. By applying association rules to cell-formation problems, certain sets of machines (machine groups) that frequently process some parts together can be inducted. A data-mining technique referred to as association rule induction is used herein to find the association rules among machines from the process database. Seventeen data sets of various size and complexity were used to evaluate the effectiveness of the proposed cell-formation algorithm based on association rule induction. The performance of the proposed approach is compared with several existing techniques. From the computational results, the proposed approach shows its ability to find quality solutions.

Job routing and operations scheduling: a network-based virtual cell formation approach

Virtual cellular manufacturing inherits the benefits of traditional cellular manufacturing and maintains the responsiveness to the changing market and routing flexibility of a job shop by integrating machine-grouping, shop layout design and intercellular flow handling. The primary goal of virtual cell formation is to minimize the throughput time of a given job. This paper proposes a method for virtual cell formation by adopting the double-sweep algorithm for the k-shortest path problem, and a heuristic is devised to schedule the virtual cells for the multiple job orders. Results generated from this method include not only the optimal candidates of the virtual cell with the shortest throughput time with sub-optimal alternative route(s) and throughput time(s) as the alternative candidates in case some resources are restricted or are not available. The procedure of virtual cell creation and scheduling is illustrated explicitly with examples. Since most of the scheduling problems are NP-hard and virtual cell scheduling is even more complex due to the bottleneck machines that are demanded by jobs at other cells. For multiplicity of possible virtual cell candidates, in addition to the precedence and resource constraints, heuristic solutions are found to be reasonable.

Design of cellular manufacturing systems in tandem configuration

This paper develops a cell formation approach for a class of cellular manufacturing systems in which intercell moves are restricted to flow in one direction from one cell to the cell immediately downstream, without backtracking. An optimal zero-one integer programming model is used to determine which machines and parts should be assigned to cells and to specify the relative position of the cells on the factory material flow pattern. The model subdivides, the underlying manufacturing system into cells based on an intercell traffic minimization criterion and subject to machine capacity and operations sequence constraints. The model also considers part setup and run times for the evaluation of capacity requirements.

Virtual manufacturing cells: exploiting layout design and intercell flows for the machine sharing problem

Existing approaches to cell formation concentrate on machine grouping and part family formation. Since their input data usually do not consider flow directions and volumes, they neglect layout and handling strategies that can simplify the machine sharing problem. Hence, these approaches fail to relate the intracell and intercell layout decisions to the machine grouping and sharing decisions. This paper introduces a new approach for cell formation which integrates machine grouping and layout design, neglecting part family formation. The concepts of a hybrid cellular layout and virtual manufacturing cells are related. It is shown that a combination of overlapping GT cells, functional layout and handling reduces the need for machine duplication among cells. This approach questions the traditional emphasis on machine duplication to create independent cells that is suggested by the standard machine-part matrix clustering methods. The steps in the method are demonstrated by using two illustrative examples obtai...