Machine Layout Problem Research Articles

An Optimal Layout Pattern-Based Solution Approach to the Extended Machine Layout Problem With Multirow Multicolumn Structure

The machine layout problem (MLP) is to determine the optimal location arrangement of machines in a production system, usually in order to minimize the total material transmission distance. This article considers a type of MLP in an automated manufacturing system with unequal-area machines, machine replicas, and taking multi-row multi-column layout structure. The aim is to determine the near-optimal machine layout and orbit layout simultaneously. We model the problem as a mixed-integer linear program by introducing the concept of orbit-based relative locations and using auxiliary binary variables, including relative location assignment variables, in-block relationship variables, and material routing variables. We further exploit the optimal layout patterns, based on which, when the relative locations of the machines and orbits are given, we can quickly derive the near-optimal absolute machine and orbit positions without solving a mixed-integer linear program. A two-layer hybrid heuristic method is proposed to solve the problem: the outer layer is a variable neighborhood search metaheuristic used to explore the solution space of the relative locations, while the inner layer is a recursive heuristic based on the optimal layout patterns. Experiments on instances of different sizes are conducted, and the effectiveness and efficiency of the proposed algorithms are verified. Note to Practitioners—Many manufacturing systems, for example, those in the semiconductor industry, use automated guided vehicles running on orbits to transfer materials between machines. The design of such a manufacturing system consists of determining the numbers of vertical and horizontal orbits, their positions, and the positions of all machines. It is not unusual for there to be hundreds of machines. Furthermore, machines of the same type can be deployed non-adjacently in an automated transfer context since materials can easily be transmitted to an arbitrary machine. The flexibility and complexity of the layout make this layout problem extremely difficult to solve. To the best of our knowledge, no dedicated study has been conducted on this issue. Additionally, state-of-the-art methodologies for related machine layout problems cannot be extended to this problem, partly because one needs to consider the material routing problem explicitly on the orbit network. In this study, we reveal the optimal layout patterns given the relative locations of machines and orbits, and we develop a recursive heuristic that is thousands of times faster than solving the corresponding mixed-integer linear program. Our proposed two-layer hybrid heuristics can solve problems with hundreds of machines, while the inner-layer problem’s precision is guaranteed to within 1%. We believe our algorithm can be used for machine and orbit layout design in flexible manufacturing systems where machine-to-machine material shipment is enables in a rectangular trasmission network.

Zoning Constrained Machine Layout Problem with Mutual Clearances

Zoning Constrained Machine Layout Problem with Mutual Clearances

Capability-based machine layout with a matheuristic-based approach

Capability-based machine layout (CB-ML) problem is firstly introduced in this paper. In the conventional machine layout problem, part flow matrix is generated from parts’ machine routes to minimize total part flows. However, defining part flow matrix based on the machines’ routes (instead of processing capability requirements of parts) restricts facility designers to utilize available flexibility in manufacturing systems. In this research, parts’ processing requirements are defined in terms of Resource Elements (REs), which describe unique processing capabilities and the processing capability overlaps of machines. If part flow matrix is defined in terms of REs, it becomes possible to utilize available flexibility in a more effective manner. However, physical part flows cannot be identified directly from the RE-based flow matrices. Because, the processing requirements of manufactured parts can be satisfied from alternative machines that contain the required REs. Therefore, RE-based part flow matrix must be mapped into the machine flow matrix, which requires defining the machine flow matrix as a decision variable. This makes the proposed CB-ML problem much more complicated than the conventional machine layout problem. We firstly developed an integer non-linear programming model for the proposed CB-ML problem. Because of its NP-completeness and nonlinear structure, a matheuristic-based solution approach is also developed. The extensive computational analysis have shown that the proposed approach is able to provide good quality solutions for the larger problem instances within reasonable computation times.

Gym Layout Modeling and Optimization

The purpose of the loop layout problem is to determine the optimal sequence for operations by giving a cyclical arrangement of the machines along a given route. Calculating the initial cost of processes is critical in general. Additionally, these expenses can be reduced by proposing an alternate flow for the system's components. It has been observed that machines at gyms are utilized in accordance with a certain program, and so they require the optimal arrangement to accommodate these programs. In this study, the best cyclical arrangement of the machines in a gym was determined using an intuitive method. Customers enrolled in various training programs will be required to change machines in accordance with the sequence of the machines in their training program. The purpose of this study is to determine the optimal layout of these machines in order to alleviate gym traffic congestion and provide a more intuitive movement plan for consumers. The purpose is to build a layout plan that minimizes backward movement using an objective function created from the positions of the machines in the training programs, the number of customers who use these programs, and the frequency with which the machines appear in multiple programs. For the first time in gyms, an effective solution to the machine layout problem has been proposed using an optimization approach.

Safety-integrated single-row machine layout problem optimization using GA and TS with a novel heuristic rule support

Safety-integrated single-row machine layout problem optimization using GA and TS with a novel heuristic rule support

Harmony search algorithm for simultaneous minimization of bi-objectives in multi-row parallel machine layout problem

Harmony search algorithm for simultaneous minimization of bi-objectives in multi-row parallel machine layout problem

An integrated approach for solving cell formation and intra-cell machine layout problem considering operation sequence and alternative process routing

An integrated approach for solving cell formation and intra-cell machine layout problem considering operation sequence and alternative process routing

Machine layout design problem under product family evolution in reconfigurable manufacturing environment: a two-phase-based AMOSA approach

Reconfigurable manufacturing systems (RMSs) are designed to manufacture a specific product, incorporating the scalability to other products in the same family. This ability is based primarily on the reconfiguration capabilities offered by reconfigurable machines tools (RMTs). This paper addresses one of the most important aspects related to the reactivity of RMSs. More specifically, it considers the relations, which link the conceived system with two important environments: its logical environment, i.e., the product family (products that share similarities) in which the RMS can evolve, and its physical environment, i.e., the physical workshop that implements this RMS. We study the machine layout problem by considering the product family evolution where two sub-problems are addressed. The first sub-problem concerns the evolution of the product, in the same family, towards new products to meet the evolutions and the requirements of the customers. The second sub-problem deals with the machine layout problem based on the results of the first sub-problem. For this, our two-phase-based approach combines the well-known metaheuristic, archived multi-objective simulated annealing (AMOSA), with an exhaustive search–based heuristic to determine the best machine layout for all the selected machines of the product family. The developed approach is based on the initially generated process plans of products (in the product family) for the RMS design under performance metrics. Moreover, the proposed layout must, at its best, respect both the constraints imposed by the generated process plans and those depicting the available location in the shop floor where machines can be placed. An illustrative numerical example is proposed to demonstrate the applicability of our approach.

A novel approach to determine the cell formation using heuristics approach

Cellular manufacturing is a vital part of lean manufacturing. It is an application of group technology. Three problems in cellular manufacturing are cell formation, machine layout and cell layout problems. However, these problems are NP-hard optimisation problems and cannot be solved using exact methods. A difficult part is to form the machine groups or cells, also called Cell Formation Problem and several techniques have been proposed to solve the same. In this paper, the Cell Formation Problem is solved using an integrated approach of heuristics along with Genetic Algorithm and Membership Index. Heuristics technique is used for domain selection which is used in Genetic Algorithm as the initial population. Genetic Algorithm is useful for optimising the results of machine assignment to cells, and Membership Index is used to assign parts to the cells. The performance is analysed using performance measures such as group technology efficiency and some exceptional elements. The proposed computational methodology is tested on standard problems of diverse size from literature papers using the hybrid approach. Results from test problems show that the proposed method is effective and efficient. The paper is useful from the practicality aspect and also relevant from current research and industry trends.

An integrated approach for solving cell formation and intra cell machine layout problem considering operation sequence and alternative process routing.

Cellular manufacturing is a group technology approach wherein parts and machines are arranged in flow production. Most of the cell formation methods in the previous literature have addressed the zero-one matrix for solving cell formation problem with single process routing. Even though multiple routings are considered in some cases, machine layout is not considered which results in increased number of backward flow, voids and exceptional elements. In this research, we have proposed a new heuristic approach for solving cell formation problem based on new similarity coefficient method and identifying intra-cell machine layout based on flow matrix by considering operation sequence and alternative routings. In order to validate the efficiency of our proposed method, five well-known test problems from the literature are employed and the results are compared with the existing method the results clearly show that the proposed approach which that provides superior or equal solution than the existing method.

A New Hybrid Approach for Machine Layout Design Under Family Product Evolution for Reconfigurable Manufacturing Systems

Reconfigurable manufacturing system (RMS) is a new paradigm that answers many of the challenges that the market nowadays imposes. In this paper, we address one of the most important aspects related to the reactivity of RMSs. We consider the relations, which link the conceived system with two important environments: its logical environment, i.e., the product family in which the RMS can evolve, and its physical environment, i.e., the physical workshop that implements this RMS. More specifically, we study the machine layout problem by considering the family product evolution where two sub-problems are considered. The first sub-problem concerns the evolution of the product, in the same family, towards new products to meet the evolutions and the requirements of the customers. The second sub-problem deals with the machine layout problem based on the results of the first sub-problem. We develop an approach which combines the well-known metaheuristic, archived multi-objective simulated annealing (AMOSA), with an exhaustive search-based heuristic to determine the best machine layout for all the selected machines of our product family. The approach is based on the initially generated process plans of products (in the product family) for the RMS design under performance metrics. The proposed layout must at its best, respects both the constraints imposed by the generated process plans and those depicting the available location in the shop floor where machines can be placed. To show the applicability of our approach, we present a simple numerical example and discuss the obtained numerical results.

A Three-Stage Approach to a Multirow Parallel Machine Layout Problem

Facility layout is vital to save operational cost and enhance production efficiency. Multirow layout is a common pattern in practical manufacturing environment. Although parallel machines are frequently implemented in practice to enhance productivity, there lacks any in-depth study on multirow layout problem with parallel machines. In this paper, its mathematical programming formulation is established to minimize material flow cost. A three-stage approach is proposed to solve it. First, a Monte Carlo heuristic is devised to optimize the sequence of machines on multiple rows. Second, a linear program is used to determine the optimal exact location of each machine. Finally, an exchange heuristic is adopted to reassign material flows among parallel machines in different machine groups. An iterative optimization strategy is suggested to execute the three stages repeatedly to improve the solution quality. This approach is applied to a number of problem instances and compared against others. The experimental results show that it is able to effectively solve this new problem and significantly decrease material flow cost. Note to Practitioners —Multirow layout is common in practical manufacturing systems in which parallel machines are often used to improve productivity, shorten production time, and guarantee some flexibility. This paper studies a multirow parallel machine layout problem that involves machine groups, each of which contains parallel machines. Solving it is to locate all machines at multiple parallel rows to minimize material flow cost. It is challenging because one needs to decompose material flows and determine exact locations of machines simultaneously. A three-stage approach is proposed to do so. It is applied to many problem instances. The results demonstrate that it works well for such layout problems with parallel machines.

Exhaustive Search Based Heuristic for Solving Machine Layout Problem in Reconfigurable Manufacturing System Design

Reconfigurable manufacturing systems (RMS) are designed to overcome the shortcomings of conventional manufacturing systems in terms of effectiveness and responsiveness facing the increasingly influencing factors imposed on the manufacturing environment by unpredictable market condition and global competition. RMS is required to be more robust, flexible and reconfigurable, which makesmachine layout problem a key step to fulfill such design. Thus, any proposed layout needs to be changeable and easily redesigned. In this paper, we consider the machine layout problem in reconfigurable context. We develop an exhaustive search based heuristic to solve it. To propose the best respective machine layout, the heuristic considers various constraints from the manufacturing environment, and the initial generated process plan for the designed RMS under performance metrics. The proposed layout must at its best, respects both the constraints imposed by the generated process plan and those depicting the available location in the shop floor where machines are going to be placed. An illustrative numerical example is proposed to demonstrate the applicability of our approach.

A memetic algorithm for the generalised machine layout problem

A memetic algorithm for the generalised machine layout problem

A memetic algorithm for the generalised machine layout problem

Designing efficient machine layouts is a key issue to ensure profitability in manufacturing environments. The major decisions in designing machine layouts are: the selection of machines (including machine replicas); the assigning of machines to the plant floor; the selection of production mix (i.e., determine the products to be produced); and the assigning of products to machines (i.e., determining the product flows). The generalised machine layout problem (GMALP) integrates these factors under a single problem. The contribution of this paper is the development of a memetic algorithm for the GMALP. The memetic algorithm takes advantage of the diversification strategies of the genetic algorithm combined with the intensification strategies of tabu search. Results obtained with the memetic algorithm compares favourably with the results presented in the literature.

The Improved Ant Colony Optimization Algorithm for MLP considering the Advantage from Relationship

An improved ant colony optimization (ACO) is presented to solve the machine layout problem (MLP), and the concept is categorized as follows: firstly, an ideology on “advantage from quantity” and “advantage from relationship” is proposed and an example is demonstrated. In addition, the strategy of attached variables under local polar coordinate systems is employed to maintain search efficiency, that is, “advantage from relationship”; thus, a mathematical model is formulated under a single rectangular coordinate system in which the relative distance and azimuth between machines are taken as attached design variables. Further, the aforementioned strategies are adopted into the ant colony optimization (ACO) algorithm, thereby employing the inverse feedback mechanism for dissemination of pheromone and the positive feedback mechanism for pheromone concentration. Finally, the effectiveness of the proposed improved ACO is tested through comparative experiments, in which the results have shown both the reliability of convergence and the improvement in optimization degree of solutions.

Efficient Machine Layout Design Method with a Fuzzy Set Theory within a Bay in a TFT-LCD Plant

In this paper, we propose an efficient machine layout design method with a fuzzy set theory within a bay in a TFT-LCD plant. An intelligent hybrid heuristic algorithm with a mixed integer linear programming (MILP) model is developed. The objective aimed to achieve is to maximize in-sequence movements and minimize backtracking movements, the total flow distance, and the total backtracking flow distance. An example is given to illustrate the proposed layout procedure. It is our hope that the proposed approaches from this study benefits TFT-LCD designers to deal with both quantitative and linguistic variables for their machine layout problems.

Solving a mathematical model integrating unequal-area facilities layout and part scheduling in a cellular manufacturing system by a genetic algorithm.

In this article, a novel integrated mixed-integer nonlinear programming model is presented for designing a cellular manufacturing system (CMS) considering machine layout and part scheduling problems simultaneously as interrelated decisions. The integrated CMS model is formulated to incorporate several design features including part due date, material handling time, operation sequence, processing time, an intra-cell layout of unequal-area facilities, and part scheduling. The objective function is to minimize makespan, tardiness penalties, and material handling costs of inter-cell and intra-cell movements. Two numerical examples are solved by the Lingo software to illustrate the results obtained by the incorporated features. In order to assess the effects and importance of integration of machine layout and part scheduling in designing a CMS, two approaches, sequentially and concurrent are investigated and the improvement resulted from a concurrent approach is revealed. Also, due to the NP-hardness of the integrated model, an efficient genetic algorithm is designed. As a consequence, computational results of this study indicate that the best solutions found by GA are better than the solutions found by B&B in much less time for both sequential and concurrent approaches. Moreover, the comparisons between the objective function values (OFVs) obtained by sequential and concurrent approaches demonstrate that the OFV improvement is averagely around 17 % by GA and 14 % by B&B.

A new approach for loop machine layout problem integrating proximity constraints

This paper focuses on the machine arrangement problem on common loop network in a flexible manufacturing system. Existing studies aim to place machines at pre-fixed positions around a loop network. This problem is considered as a permutation problem that aims to find the best combination to reduce generated costs. In this work, we try to add more complexity to this problem by respecting the proximity constraints, defined by the experts, between the machines. To do this, we propose an algorithm based on direct distance measure. Logically, proximity constraints are checked using direct distances but costs are calculated using travelled distances. Throughout this study, we seek the best machine layout in four transport system configuration types to minimise the sum of flow time distances. Comparing our algorithm results with two hybrid genetic algorithms, the empirical results show that the proposed algorithm provides the most suitable solutions.

Approaches to solve cell formation, machine layout and cell layout problem: A Review

Cell formation, machine layout and cell layout problems in cellular manufacturing system are NP-Complete optimization problems. Good cell formation & layout design in cellular manufacturing system is achieved by finding optimum or near-optimum solutions of these problems, which substantially reduces manufacturing cost and time. Many approaches have been advocated by researchers to obtain better cell formation & layout design. An attempt has been done in this paper to review such approaches based on heuristics, meta-heuristics, hybrid methods and exact solution methods developed by past researchers to solve these problems. The main objective of this review paper is to find out the effective and efficient approaches by comparing them based on performance criteria, their benefits and drawbacks in solving cellular manufacturing system problems and find out future research scope in this area.