Approaches to uncertainties in facility layout problems: Perspectives at the beginning of the 21<Superscript>st</Superscript> Century

Production uncertainty is one of the most challenging aspects in manufacturing environments in the 21st century. The next generation of intelligent manufacturing is dynamically depending on the production requirements, and success in designing agile facilities is closely related to what extent these requirements are satisfied. This paper presents the most recent advancements in designing robust and flexible facilities under uncertainty. The focus is on exploring the way uncertainty is incorporated in facility design, namely dynamic and stochastic facility layout problems. Recent approaches are explored and categorized in detail, and previous approaches are briefly reviewed in the related categories. Furthermore, research avenues warranting exploration in the emerging field of facility design are also discussed.     

A simulated annealing algorithm for dynamic layout problem

Increased level of volatility in today's manufacturing world demanded new approaches for modelling and solving many of its well-known problems like the facility layout problem. Over a decade ago Rosenblatt published a key paper on modelling and solving dynamic version of the facility layout problems. Since then, various other researchers proposed new and improved models and algorithms to solve the problem. Balakrishnan and Cheng have recently published a comprehensive review of the literature about this subject. The problem was defined as a complex combinatorial optimisation problem. The efficiency of SA in solving combinatorial optimisation problems is very well known. However, it has recently not been applied to DLP based on the review of the available literature. In this research paper a SA-based procedure for DLP is developed and results for test problems are reported.

Scope and purpose

One of the characteristic of today's manufacturing environments is volatility. Under a volatile environment (or dynamic manufacturing environment) demand is not stable. To operate efficiently under such environments facilities must be adaptive to changing demand conditions. This requires solution of the dynamic layout problem (DLP). DLP is a complex combinatorial optimisation problem for which optimal solutions can be found for small size problems. This research paper makes use of a SA algorithm to solve the DLP. Simulated annealing (SA) is a well-established stochastic neighbourhood search technique. It has a potential to solve complex combinatorial optimisation problems. The paper presents in detail how to apply SA to solve DLP and an extensive computational study. The computational study shows that SA is quite effective in solving dynamic layout problems.     

制造系统中的单向环型设备布局设计

提出一种优化建模与虚拟现实技术相结合的求解策略，较好地解决了制造系统中的单向环型设备布局问题．研究该问题的固有特性，提出三条定理，构建了一个启发式算法，并实现了一个沉浸式虚拟布局设计的例子．     

Towards measuring the effectiveness of a facilities layout

Performance measurement models are essential to support various decision making problems that may arise during life cycle of a facilities layout. Available models are only suitable for early stages in the design phase of life cycle. However, measurement models have a great consequence in other phases also such as production planning, control and when modification to be incorporated due to the changes in market demand, which happens very often in today's global competition. In addition, the existing models have considered only material handling cost as the performance measurement factor. Nevertheless, the empty travel of material handling equipment, layout flexibility and area utilisation have a significant contribution towards the layout effectiveness. It is therefore necessary to have a measurement model to determine the facilities layout's effectiveness by considering all significant factors. A measurement model considering a set of three layout effectiveness factors—facilities layout flexibility (FLF), productive area utilisation (PAU) and closeness gap (CG)—is developed in our research. The proposed model will enable the decision-maker of a manufacturing enterprise to analyse a layout in three different aspects, based on which they can make decision towards productivity improvement. This paper mainly discusses about the measurement of the CG. The CG is developed with respect to the objective of bringing closer the highly interactive facilities/departments. The CG presented in this paper extends other related works by incorporating numerous aspects of layout that include empty travel of material handling equipment, information flow, personnel flow and equipment flow.     

Solving a group layout design model of a dynamic cellular manufacturing system with alternative process routings,lot splitting and flexible reconfiguration by simulated annealing

This paper presents a novel mixed-integer non-linear programming model for the layout design of a dynamic cellular manufacturing system (DCMS). In a dynamic environment, the product mix and part demands are varying during a multi-period planning horizon. As a result, the best cell configuration for one period may not be efficient for successive periods, and thus it necessitates reconfigurations. Three major and interrelated decisions are involved in the design of a CMS; namely cell formation (CF), group layout (GL) and group scheduling (GS). A novel aspect of this model is concurrently making the CF and GL decisions in a dynamic environment. The proposed model integrating the CF and GL decisions can be used by researchers and practitioners to design GL in practical and dynamic cell formation problems. Another compromising aspect of this model is the utilization of multi-rows layout to locate machines in the cells configured with flexible shapes. Such a DCMS model with an extensive coverage of important manufacturing features has not been proposed before and incorporates several design features including alternate process routings, operation sequence, processing time, production volume of parts, purchasing machine, duplicate machines, machine capacity, lot splitting, intra-cell layout, inter-cell layout, multi-rows layout of equal area facilities and flexible reconfiguration. The objective of the integrated model is to minimize the total costs of intra and inter-cell material handling, machine relocation, purchasing new machines, machine overhead and machine processing. Linearization procedures are used to transform the presented non-linear programming model into a linearized formulation. Two numerical examples taken from the literature are solved by the Lingo software using a branch-and-bound method to illustrate the performance of this model. An efficient simulated annealing (SA) algorithm with elaborately designed solution representation and neighborhood generation is extended to solve the proposed model because of its NP-hardness. It is then tested using several problems with different sizes and settings to verify the computational efficiency of the developed algorithm in comparison with the Lingo software. The obtained results show that the proposed SA is able to find the near-optimal solutions in computational time, approximately 100 times less than Lingo. Also, the computational results show that the proposed model to some extent overcomes common disadvantages in the existing dynamic cell formation models that have not yet considered layout problems.     

Design of a suitable production management system for a manufacturing company

This paper reports on the design of a suitable production management system (PMS) for a manufacturing company, located in Western Australia. The company was experiencing problems in scheduling and plant layout leading to further problems in materials flow, labour control, inventory and purchasing, material handling system, and production space.

Group technology (GT) was used to design a new plant layout. A G.T. algorithm was developed to minimise machine duplications. A Kanban system was designed to assist execution of scheduling based on a pull system. The design was tested by simulation using actual data collected on existing operations.     

Agility and production flow layouts: An analytical decision analysis

The term ‘agile manufacturing’ has referred to operational aspects of a manufacturing company concerning their ability to produce customized products at mass production prices and with short lead times. A core issue faced within agile manufacturing is the need for appropriate and supporting production and operations systems. Many design dimensions of agility and agile manufacturing exist. To help attain this goal for integrating the many design dimensions, operations infrastructure and capacity must be carefully planned to manage production flow, and thus production layout planning takes on an increasingly important role. Given the importance of these dimensions in response to agility, this paper seeks to make a contribution by providing insights into a decision aid for evaluating production flow layouts that support and enhance the agile manufacture of products. Layout design has a significant impact on the performance of a manufacturing or service industry system and has been an active research area for many decades. Strategic evaluation of production layouts requires consideration of both qualitative and quantitative factors (managerial, organizational, and technical). This paper makes use of the Analytical Network Process (ANP) which captures interdependencies among different criteria, sub-criteria and dimensions, an evident characteristic of production flow layouts in complex agile manufacturing environments. An application case study exemplifying the practical usefulness of this type of model describes how management, after implementation of the model, made a mid-course correction related to the production layout initially selected.     

制造系统的可重构布局设计

研究重构系统的新布局具有重要的理论与实际意义 .本文讨论了制造系统可重构布局研究的目标、对象、基础及研究范畴 ,提出了利用模拟退火方法寻找重构布局最优解的搜索算法 .仿真实验验证了算法的有效性     

An Electromagnetism-like algorithm for cell formation and layout problem

Implementation of cellular manufacturing systems (CMS) is thriving among manufacturing companies due to many advantages that are attained by applying this system. In this study CMS formation and layout problems are considered. An Electromagnetism like (EM-like) algorithm is developed to solve the mentioned problems. In addition the required modifications to make EM-like algorithm applicable in these problems are mentioned. A heuristic approach is developed as a local search method to improve the quality of solution of EM-like. Beside in order to examine its performance, it is compared with two other methods. The performance of EM-like algorithm with proposed heuristic and GA are compared and it is demonstrated that implementing EM-like algorithm in this problem can improve the results significantly in comparison with GA. In addition some statistical tests are conducted to find the best performance of EM-like algorithm and GA due to their parameters. The convergence diagrams are plotted for two problems to compare the convergence process of the algorithms. For small size problems the performances of the algorithms are compared with an exact algorithm (Branch & Bound).     

Nature inspired algorithms to optimize robot workcell layouts

Multi-objective layout optimization methods for the conceptual design of robot cellular manufacturing systems are proposed in this paper. Robot cellular manufacturing systems utilize one or more flexible robots which can carry out a large number of operations, and can conduct flexible assemble processes. The layout design stage of such manufacturing systems is especially important since fundamental performances of the manufacturing system under consideration are determined at this stage. Layout area, operation time and manipulability of robot are the three important criteria when it comes to designing manufacturing system. The use of nature inspired algorithms are not extensively explored to optimize robot workcell layouts. The contribution in this paper is the use of five nature-inspired algorithms, viz. genetic algorithm (GA), differential evolution (DE), artificial bee colony (ABC), charge search system (CSS) and particle swarm optimization (PSO) algorithms and to optimize the three design criteria simultaneously. Non-dominated sorting genetic algorithm-II is used to handle multiple objectives and to obtain pareto solutions for the problems considered. The performance of sequence pair and B*-Tree layout representation schemes are also evaluated. It is found that sequence pair scheme performs better than B*-Tree representation and it is used in the algorithms. Numerical examples are provided to illustrate the effectiveness and usefulness of the proposed methods. It is observed that PSO performs better over the other algorithms in terms of solution quality.     

Development and Applications of Holonic Manufacturing Systems: A Survey

This paper surveys the literature in the holonic manufacturing systems area in an attempt to bring together the key issues in the development and applications of holonic systems. A brief introduction presents the characteristics of today’s manufacturing environment and the requirements for next generation manufacturing systems. Then, starting with considerations about the origins of the holonic concept and its first applications in manufacturing, the paper presents the advances made in applying the holonic concept to manufacturing systems area. Several considerations for the development of holonic manufacturing systems and specific holonic system requirements are discussed. As holonic concept is considered a solution for next generation manufacturing systems, there is a significant number of applications and implementations of the holonic concept in manufacturing systems domain. The most important and relevant approaches developed so far are presented. Finally, a short conclusion and future research directions in the area are provided     

A simulated annealing heuristic for the dynamic layout problem with budget constraint

Facility layout problem has been extensively studied in the literature because the total material handling cost can be a significant portion in the operational costs for a company and in the manufacturing cost of a product. Today’s severe global competition, rapid changes in technology and shortening life cycle of products force companies to evaluate and modify their facility layout in a periodic fashion. This type of layout problems is categorized as the dynamic facility layout problem (DFLP). As a realistic dimension of the problem, one has to consider also the limited budget to cover the cost of changing the layout. In this study, we propose a simulated annealing heuristic for the DFLP with budget constraint, and show the effectiveness of this heuristic on a set of numerical experiments.     

Mathematical formulation and a new metaheuristic for the constrained double-floor corridor allocation problem

A layout plan for a manufacturing system that is designed without any facility constraints will most likely be infeasible when confronted with reality. Additionally, considering that land available for building industrial plants is limited and its cost is high, it is necessary to investigate the layout planning of two and multi-floor facilities. To address these shortages in the scientific literature, we focus on the double-floor corridor allocation problem (DFCAP) which covers a wide range of complex facility constraints, such as fixed floor constraints, fixed row constraints, fixed positioning constraints, mutual floor constraints, mutual row constraints, sequencing constraints and adjacency constraints. For the model mentioned above, we term it as a constrained DFCAP (cDFCAP). A mixed-integer linear programming model is formulated for the cDFCAP. In order to solve larger realistic problems, a constrained metaheuristic with the memetic algorithm framework customised for solving the cDFCAP is introduced in this work. In our algorithm, four problem-specific heuristic rules to construct a set of initial solutions are developed. In addition, an ideal parameter combination for our constrained memetic algorithm is determined through a Taguchi experimental design. Finally, the results of a set of cDFCAP instances with different sizes (n = 10∼80) report that our provided approach is effective for the considered problem.     

A concurrent solution for intra-cell flow path layouts and I/O point locations of cells in a cellular manufacturing system

In this paper, we study the I/O (Input/Output) point location problem and the intra-cell flow path layout problem of cells in a cellular manufacturing system. Traditional approaches have often solved these two problems as separate problems, despite they are mutually affected. As a result, the results obtained by traditional approaches may not be as desirable as expected. In this study, we propose a layout procedure that can solve these two problems concurrently, so that the sum of the inter-cell flow distance and the intra-cell flow distance can be minimized. We assume cells have been arranged along a straight-line inter-cell flow path. Furthermore, the machines’ positions on each cell’s intra-cell flow path have been determined, but the intra-cell flow path of each cell has not been placed on the shop floor yet. We also assume the configuration of intra-cell flow paths is serpentine. The proposed layout procedure classifies the flow distance incurred by inter-cell flow into five types and minimizes them with different solution procedures containing various linear programming models. The proposed layout procedure has four phases. At the first phase, we find each cell’s input and output points on the inter-cell flow path by considering only the inter-cell flow distance. At the second phase, we find the input and outpoint points on each cell’s intra-cell flow path by considering only the intra-cell flow distance. At the third phase, we use the points found in the previous two phases as references to help us correctly orient and arrange each cell’s intra-cell flow path on the shop floor. Finally, at the fourth phase, we find the accurate the input points and output points on each cell’s intra-cell flow path and the inter-cell flow path by simultaneously considering the inter-cell and the intra-cell flow distance. We use an example to illustrate the proposed layout procedure. The results of the example show that the proposed layout procedure can effectively find each cell’s I/O point locations and intra-cell flow path layout by considering both intra-cell and inter-cell flow distance at the same time.     

Solving an extended multi-row facility layout problem with fuzzy clearances using GA

Multi-row facility layout problem (MRFLP) is a class of facility layout problems, which decides upon the arrangement of facilities in some fixed numbers of rows in order to minimize material handling cost. Nowadays, according to the new layout requirements, the facility layout problems (FLPs) have many applications such as hospital layout, construction site layout planning and layout of logistics facilities. Therefore, we study an extended MRFLP, as a novel layout problem, with the following main assumptions: 1) the facilities are arranged in a two-dimensional area and without splitter rows, 2) multiple products are available, 3) distance between each pair of facilities, due to inaccurate and flexible manufacturing processes and other limitations (such as WIPs, industrial instruments, transportation lines and etc.), is considered as fuzzy number, and 4) the objective function is considered as minimizing the material handling and lost opportunity costs. To model these assumptions, a nonlinear mixed-integer programming model with fuzzy constraints is presented and then converted to a linear mixed-integer programming model. Since the developed model is an NP-hard problem, a genetic algorithm approach is suggested to find the best solutions with a minimum cost function. Additionally, three different crossover methods are compared in the proposed genetic algorithm and finally, a sensitivity analysis is performed to discuss important parameters.     

Solving the design of distributed layout problem using forecast windows: A hybrid algorithm approach

In today’s competitive environment, manufacturing facilities have to be more responsive to the frequent changes in product mix and demand by realigning their organizational structure for minimizing material handling cost. However, manufacturing firms are reluctant to modify the layout as it leads to operation disruption and excess rearrangement cost. In this paper, we present an alternative approach for designing a multi-period layout (i.e., distributed layout) that maintains a tradeoff between re-layout cost and cost of excess material handling. Obtaining an optimal solution to distributed layout problem is generally a difficult task, owing to larger size of quadratic assignment problem. In order to overcome the aforementioned drawback, a meta-heuristic, named ‘CSO-DLP’ (Clonal Symbiotic Operated-Distributed Layout Planning) is developed for designing a distributed layout that jointly determines the arrangement of department and flow allocation among them. It inherits its trait from Symbiotic algorithm and Clonal algorithm. In addition to these; the concept of ‘forecast window’ is used, which evaluates the layout for varying number of periods at a given time. The proposed meta-heuristic is applied on a benchmark dataset and the effect of system parameters, such as rearrangement cost, department disintegration, and duplication are investigated and benchmarked in this paper.     

Multiple-attribute decision making methods for plant layout design problem

The layout design problem is a strategic issue and has a significant impact on the efficiency of a manufacturing system. Much of the existing layout design literature that uses a surrogate function for flow distance or for simplified objectives may be entrapped into local optimum; and subsequently lead to a poor layout design due to the multiple-attribute decision making (MADM) nature of a layout design decision. The present study explores the use of MADM approaches in solving a layout design problem. The proposed methodology is illustrated through a practical application from an IC packaging company. Two methods are proposed in solving the case study problem: Technique for order preference by similarity to ideal solution (TOPSIS) and fuzzy TOPSIS. Empirical results showed that the proposed methods are viable approaches in solving a layout design problem. TOPSIS is a viable approach for the case study problem and is suitable for precise value performance ratings. When the performance ratings are vague and imprecise, the fuzzy TOPSIS is a preferred solution method.     

Optimisation of a Simulated-Annealing-based Heuristic for Single Row Machine Layout Problem by Genetic Algorithm

We discuss a procedure to determine the optimal set of parameters relevant to heuristics based on the Simulated Annealing technique, an algorithm which is widely applied to combinatorial problems in the field of manufacturing systems. We consider the search for the best set as a second optimisation problem that we solve by a Genetic Algorithm. The performance of our approach is tested in the particular case of backtracking minimisation in a single row machine layout problem for flexible manufacturing systems.     

(Deep) Reinforcement learning for electric power system control and related problems: A short review and perspectives

This paper reviews existing works on (deep) reinforcement learning considerations in electric power system control. The works are reviewed as they relate to electric power system operating states (normal, preventive, emergency, restorative) and control levels (local, household, microgrid, subsystem, wide-area). Due attention is paid to the control-related problems considerations (cyber-security, big data analysis, short-term load forecast, and composite load modelling). Observations from reviewed literature are drawn and perspectives discussed. In order to make the text compact and as easy as possible to read, the focus is only on the works published (or “in press”) in journals and books while conference publications are not included. Exceptions are several work available in open repositories likely to become journal publications in near future. Hopefully this paper could serve as a good source of information for all those interested in solving similar problems.     

基于改进人工蜂群算法的体声波滤波器自动布局

针对体声波（BAW）滤波器布局中芯片面积利用率低、设计周期长、制造成本高等问题,提出了一种基于改进人工蜂群算法的BAW滤波器自动布局方法。首先构建了自动布局的评价模型,通过结合利用圆形容器的顺序布局和基于旋转角度编码的聚拢布局来简化自动布局的难度;同时采用了一种改进人工蜂群算法去搜寻BAW滤波器的最优顺序布局和聚拢布局方案;最后,结合多组BAW滤波器的设计案例验证自动布局算法的有效性,其布局有效面积占比提升约17%,整体布局呈方形,且完成滤波器的自动布局仅需30 min。结果表明在保证BAW滤波器性能的前提下,算法可有效提升芯片面积利用率、大幅缩减滤波器的设计周期。