The generalized machine layout problem.

This paper analyzes the machine layout problem in flexible manufacturing systems (FMS's). We show that the quadratic assignment formulation cannot be used to model the machine layout problem. Four basic types of machine layouts that are frequently encountered in FMS's are presented. A measure to determine the relationship between machines is introduced. Since automated guided vehicles are commonly used to transport material between machines, their motion characteristic is discussed. Two new construction algorithms are presented to solve the machine layout problem in FMS's. They generate solutions with acceptable quality in low computational time. The triangle assignment algorithm (TAA) is compared to existing methods for 8 test problems and is found to give solutions of better quality than any other construction method published. When compared to existing methods, the computation time performance is attractive.

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

A solution to the facility layout problem using simulated annealing

Machine layout and material flow between machines are crucial considerations for improving productivity in any manufacturing environment. The machine layout and the operations assignment problems are both known to be NP hard problems. In this paper, we consider a combined machine layout and job assignment problem and introduce an evolutionary algorithm to solve this combined problem. The usefulness of our approach is demonstrated through numerical examples.

The Machine Layout Problem (MLP) is faced with two difficulties: first, the uncertainty of constringency in mathematical methodology and second, the difficulty in accuracy location. This research takes the advantage of the polar coordinates system, which can well keep the relative hereditary factors in the design variables, to solve the problem of constringency, and takes the virtual reality technology to solve the problem of visualised detailed location. First, the construction of optimisation model for MLP is proposed, and then based on which the polar coordinates-based Genetic Algorithm (GA) methodology is presented to improve the efficiency of constringency. Second, the virtual layout tactics are proposed to realise the visualised accuracy location, which take the results from GA as initial values. Contrastive experiments demonstrate the combination of the polar coordinates-based GA and the virtual layout has improved the efficiency of constringency and the practical function of detailed locations.

Cell formation and machine layout in cellular manufacturing systems (CMs) design are considered as a crucial, yet hard and complex decision process. Owing to the nondeterministic polynomial time (NP) and combinatorial class of this problem, this paper presents an innovative heuristic approach to re‐arrange machines enabling the minimisation of inter/intra‐ cellular movements as well as the cost of material handling between machines, therefore increasing group efficiency and efficacy. The heuristic approach, which is based on group technology, genetic algorithms, and desirability function, determines the optimal solution for flexible cell formation and machine layout within each cell. Flexibility refers to an explicit improvement using the desirability function to modify cell design by altering the ratio data; that is, the weight factor to meet demand flexibility. Specifically, the desirable function proposed here to provide the optimal setting of the weighting factor as a key factor which enables CMs design the flexibility to control the cell size. Promised results were obtained when the proposed approach was applied to a case study. Practical implications and recommendations are provided for use by decision makers in the design of CMs.

Machine layout with a linear single-row flow path in an automated manufacturing system

This paper focuses on solving the Continuous Facility Layout Problem (CFLP), which aims to minimize material handling costs by strategically placing facilities in a known or unknown area. The objective is to find optimal or near-optimal facility arrangements while adhering to non-overlapping and spatial constraints, thus enhancing the efficiency of production systems. The study addresses various layout scenarios, including single-row facility layout (with and without clearance), continuous layout, and unequal-area facility layout problems. To achieve this, the authors propose a mixed-integer nonlinear programming (MINLP) model tailored for continuous layouts. Two meta-heuristic algorithms are developed to optimize this model: a hybrid Simulated Annealing-Genetic Algorithm (SA-GA), which leverages genetic crossover operations, and an Enhanced Harmony Search Algorithm (EHSA), featuring dynamic parameters and a novel improvisation technique. The proposed methods provide flexible and efficient solutions for both small and large-scale layout problems, offering decision-makers practical tools for real-world applications.

Since Facility Layout Problem (FLP) affects the total manufacturing cost significantly, it can be considered as a critical issue in the early stages of designing Flexible Manufacturing Systems (FMSs), particularly in volatile environments where uncertainty in product demands is inevitable. This paper proposes a new mathematical model by using the Quadratic Assignment Problem formulation for designing an optimal machine layout for each period of a dynamic machine layout problem in FMSs. The product demands are considered as independent normally distributed random variables with known Probability Density Function (PDF), which changes from period to period at random. In this model, the decision maker's defined confidence level is also considered. The confidence level represents the decision maker's attitude about uncertainty in product demands in such a way that it affects the results of the problem significantly. To validate the proposed model, two different size test problems are generated at random. Since the FLP, especially in multi-period case is a hard Combinatorial Optimization Problem (COP), Simulated Annealing (SA) meta-heuristic resolution approach programmed in Matlab is used to solve the mathematical model in a reasonable computational time. Finally, the computational results are evaluated statistically.

This paper addresses a crane scheduling and machine layout problem in a Computer Integrated Manufacturing (CIM) Environment. A single crame is used to move all the Work-in-Process (WIP) in the system. The overall system objective is to maximize the yield rate subject to the flow time limit of the WIP. We formalize the problem, and analytically and empirically show that cyclic scheduling provides a near optimal solution, which is superior to dispatching rules. First, we illustrate the optimality and benefits of cyclic scheduling in a simple environment. Then, for multiple-product problems, we show that for a given sequence, finding the minimum cycle time becomes the maximum cost circular network flow problem in a graph. Based on the insights developed, a heuristic for sequencing product types in a cycle is derived that approximately minimizes the cycle time over all sequences. Finally, computational experiments are reported and various assertions made in the paper are empirically verified.

The layout problem is one of important decision in cellular manufacturing systems (CMS). After deciding the cells and the intercellular movements in the cell formation stage, it is necessary to do proper layout of machines to get effective utilization of CMS. Proper layout will minimize material handling cost to a greater extent. In this paper, a mathematical formulation is presented. As it is NP-hard, a genetic algorithm is adopted as solution methodology. In order to validate the performance of the algorithm a well-known quadratic assignment problems (QAP) that deal with location are taken for testing, which shows that the proposed methodology provides promising results. The effectiveness of GA approach is evaluated with numerical examples. The cost performance is compared with other approaches. The intra cell layout problem is discussed.

New complexity measures for the facility layout problem: an empirical study using traditional and neural network analysis

The unequal area facility layout problem (UA-FLP) refers to the reasonable arrangement of a certain number of facilities in a given layout area. The facility layout should satisfy given layout constraints and optimize given optimization objectives as far as possible. In this paper, a method combining improved lowest horizontal line method and particle swarm optimization algorithm is proposed to solve UA-FLP, which achieves multi-objective optimization of material handling cost, the adjacent value and the utilization rate of floor shop. On the one hand, the algorithm formulates facility packing rules through the improved lowest horizontal line method, which simplifies the legalization of facility layout. On the other hand, a modified particle swarm optimization (PSO) algorithm combining objective space division method (OSD) and niche technology is used for multi-objective optimization. The proposed algorithm overcomes the shortcomings of previous facility layout methods such as complex overlapping interference process, large amount of calculation and long time for multi-objective optimization. Compared with the comparison methods, the results show that material handling cost is reduced by 1%–6% and the utilization ratio of floor shop is increased by 2%–7%.

An efficient facility layout is crucial for improving productivity and operational efficiency, especially for Small and Medium Enterprises like CV. XYZ, which face space limitations and inefficient material flow. This study aims to redesign the facility layout using the Systematic Layout Planning (SLP) method to optimize material flow, reduce internal transportation, and enhance the competitiveness of CV. XYZ in the screen printing industry. A quantitative descriptive approach was employed, with data collected through observations, interviews, documentation, and literature review. The SLP stages include activity analysis, calculation of Material Handling Costs (MHC), creating a from-to chart, priority scale table, activity relationship chart, and layout simulation using Blocplan software. The results show that the proposed layout successfully reduced the distance between workstations, optimized the process flow, and decreased MHC by 7% or IDR 15,648.75. These changes enhanced production efficiency, minimized material handling time, and created a more organized and productive layout. By effectively redesigning the facility layout, CV. XYZ improved its operational efficiency.

For facility layout problem with continuous block and unequal area, it is key to generate feasible solution of facility layout with arbitrary space form in order to find the optimal arrangement scheme under a given goal. According to the given slicing position and slicing mode, the plane for arrangement was divided into many block areas by use of plane segmentation, which was consistent with the facilities in number. The precise coordinates of the lower-left corner and the top-right corner of each facility were calculated in light of its area, width, and length. The corresponding algorithm was designed in the form of pseudocode. The procedure proposed can provide a feasible facility layout solution. The running results of facilities layout instance containing 14 facilities show that the scheme can output facilities plane layout scheme quickly and provide decision support for the facilities planning.