Facility layout problem: Bibliometric and benchmarking analysis

Facility layout problem is related to the location of departments in a facility area, with the aim of determining the most effective configuration. Researches based on different approaches have been published in the last six decades and, to prove the effectiveness of the results obtained, several instances have been developed. This paper presents a general overview on the extant literature on facility layout problems in order to identify the main research trends and propose future research questions. Firstly, in order to give the reader an overview of the literature, a bibliometric analysis is presented. Then, a clusterization of the papers referred to the main instances reported in literature was carried out in order to create a database that can be a useful tool in the benchmarking procedure for researchers that would approach this kind of problems

New Mixed Integer Programming for Facility Layout Design without Loss of Department Area

This paper proposes a New Mixed Integer Programming (NMIP) for solving facility layout problem (FLP). The formulation is extensively tested on problems from literature to minimize material handling cost when addresses on the shop floor. Every department and shop floor in tested problem were fixed dimension of length and width. Classic Mixed Integer Programming (MIP) solves FLP with fixed layout area and preset each department’s lower-upper limit of length and width. As a result, there might be some departments with 5-10% area less than initial layout design requirements which leads to problem in design and construction process. It is infeasible to address the department on the actual shop floor thus adjustment of result from MIP is required. The main purpose of NMIP is to eliminate such infeasibility and show the efficiency of this model. Keywords: mixed integer programing, facility layout design, facility layout problem, heuristic

Designing Facilities to Improve Flexibility: Zone-based Dynamic Facility Layout with Embedded Input/Output Points

This paper considers solving the unequal area Dynamic Facility Layout Problem (DFLP) using a zone-based structure. Zone-based layouts have significant advantages, such as being easily transferable to a detailed layout with innately included possible aisle structures; therefore, they can be fitted to the unique needs of the layout designers. The unequal area DFLP is modeled and solved using a zone-based structure, which is referred to as ZDFLP, where the dimensions of the departments and material handling system input/output (I/O) points are decision variables. A two-phase matheuristic, which directly operates on Problem ZDFLP without requiring an encoding scheme of the problem, is proposed to solve the ZDFLP with promising results

Designing Facilities to Improve Flexibility: Zone-based Dynamic Facility Layout

This paper considers solving the unequal area Dynamic Facility Layout Problem (DFLP) using a zone-based structure. Zone-based layouts have significant advantages, such as being easily transferable to a detailed layout with innately included possible aisle structures; therefore, they can be fitted to the unique needs of the layout designers. The unequal area DFLP is modeled and solved using a zone-based structure, which is referred to as ZDFLP, where the dimensions of the departments and material handling system input/output (I/O) points are decision variables. A two-phase matheuristic, which directly operates on Problem ZDFLP without requiring an encoding scheme of the problem, is proposed to solve the ZDFLP with promising results

Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions

Sem PDF conforme despacho. Fundacao para a Ciencia e a Tecnologia - PEstOE/MAT/UI0297/2014.Facility layout problems are an important class of operations research problems that has been studied for several decades. Most variants of facility layout are NP-hard, therefore global optimal solutions are difficult or impossible to compute in reasonable time. Mathematical optimization approaches that guarantee global optimality of solutions or tight bounds on the global optimal value have nevertheless been successfully applied to several variants of facility layout. This review covers three classes of layout problems, namely row layout, unequal-areas layout, and multifloor layout. We summarize the main contributions to the area made using mathematical optimization, mostly mixed integer linear optimization and conic optimization. For each class of problems, we also briefly discuss directions that remain open for future research.publishe

The aperiodic facility layout problem with time-varying demands and an optimal master-slave solution approach

In many seasonal industries, customer demands are constantly changing over time, and accordingly the facility layout should be re-optimized in a timely manner to adapt to changing material handling patterns among manufacturing departments. This paper investigates the aperiodic facility layout problem (AFLP) that involves arranging facilities layout and re-layout aperiodically in a dynamic manufacturing environment during a given planning horizon. The AFLP is decomposed into a master problem and a combination set of static facility layout problems (FLPs, the slave problems) without loss of optimality, and all problems are formulated as mixed-integer linear programming (MILP) models that can be solved by MIP solvers for small-sized problems. An exact backward dynamic programming (BDP) algorithm with a computational complexity of O(n 2) is developed for the master problem, and an improved linear programming based problem evolution algorithm (PEA-LP) is developed for the traditional static FLP. Computational experiments are conducted on two new problems and twelve well-known benchmark problems from the literature, and the experimental results show that the proposed solution approach is promising for solving the AFLP with practical sizes of problem instances. In addition, the improved PEA-LP found new best solutions for five benchmark problems

Concurrent design of facility layout and flow-based department formation

The design of facility layout takes into account a number of issues including the formation of departments, the layout of these, the determination of the material handling methods to be used, etc. To achieve an efficient layout, these issues should be examined simultaneously. However, in practice, these problems are generally formulated and solved sequentially due to the complicated nature of the integrated problem. Specifically, there is close interaction between the formation of departments and layout of these departments. These problems are treated as separate problems that are solved sequentially. This procedure is mainly due to the complexity of each problem and the interrelationships between them. In this research, we take a first step toward integrating the flow-based department formation and departmental layout into comprehensive mathematical models and develop appropriate solution procedures. It is expected that these mathematical models and the solution procedures developed will generate more efficient manufacturing system designs, insights into the nature of the concurrent facility layout problem, and new research directions

Non-traditional Aisle Design for a Manufacturing Facility Layout

Methods for designing a facility layout typically assume that the aisles for interdepartmental travel will be parallel to the exterior walls of the facility. However, by putting aisles at an angle to the exterior walls, more direct routes between departments can be created, reducing travel distance. This paper describes a method to create a facility layout that does not have orthogonal aisles and testing of the resulting layouts shows that travel distance is reduced

디스플레이 산업의 스토커와 기둥 구조를 고려한 설비 최적 배치 모델링

학위논문(석사) -- 서울대학교대학원 : 공학전문대학원 응용공학과, 2023. 2. 문일경.In the display manufacturing system, the optimal facility layout can maximize productivity with minimal investment cost by efficiently utilizing a fabrication (FAB) area. Because the project period is insufficient to analyze all scenarios of the new layout, industrial engineers are instead arranging facilities based on past experience and their planning rules. The aim of this study is to design the optimal facility layout automatically for processes and automated material handling systems, such as stockers and vehicles, that can satisfy the material handling cost while avoiding overlap with pillars. We developed a mathematical programming model and found an optimal layout with CPLEX optimization software that minimizes the material handling cost for test instances. The optimal results showed great effects in transportation time and the distance, the traffic volume, and the material handling investment costs. This indicates that there is a possibility of obtaining an optimal layout within a reasonable time frame when planning a new factory and suggests that engineers can make more objective and reliable decisions through given results.디스플레이 제조 시스템에서 최적의 설비 배치는 한정된 공장내 영역을 효율적으로 활용하여 최소의 투자 비용으로 제조 생산성을 극대화 시킬 수 있다. 산업 엔지니어들은 초기 기획단계에서 목적에 부합하는 레이아웃을 설계하기 위해 노력하지만, 모든 시나리오를 분석하여 최적안을 결정하기에는 프로젝트 기간이 매우 부족하기 때문에 그 대신, 과거 경험과 엔지니어의 규칙에 기반하여 최적 설비 배치안을 제안하고 있다. 이를 해결하기 위해 우리는 설비 레이아웃 문제를 수학적으로 접근하여, 최적 위치에 설비를 배치하는 모형을 제안한다. 모델은 공장을 지탱하는 기둥과의 간섭을 회피하면서 한정된 공간내 공정 설비들과 물류시스템을 효율적으로 배치하며, 특히, 디스플레이 물류의 큰 비중을 차지하는 스토커와 비클 시스템을 함께 고려한다. 우리는 CPLEX 최적화 소프트웨어를 사용하여 테스트 인스턴스 대해 물류 운송 비용을 최소화하는 최적의 레이아웃을 설계하였다. 최적 설비 배치 결과는 운송 시간 및 거리, 물류시스템의 교통량, 그리고 물류 투자비용 측면에서 큰 효과를 보였다. 이 모델은 주어진 프로젝트 기간 내에 공장의 기둥과 고도화된 물류 시스템을 고려한 설비 배치 문제를 제안할 수 있으며, 엔지니어는 자동으로 출력되는 결과를 통해 보다 객관적이고 신뢰할 수 있는 의사 결정을 할 수 있음을 시사한다.I. Introduction 1 1.1 Background of Study 1 1.2 Literature Review 2 1.3 Purpose of Research 6 II. Characteristics of Display FAB 8 2.1 Layout Planning 8 2.2 Basic Layout Types 10 2.3 Display Manufacturing System 12 III. Model Formulation 15 3.1 Problem Definition 15 3.2 Notations and Formulation 20 3.3 Solution Approach 36 IV. Computational Experiments 38 4.1 CPLEX Optimizer Model 39 4.2 Test Instances 42 4.3 Experiment Results 48 V. Conclusions 52 Bibliography 54 Abstract 57석