Mitigation of risk in facility layout design for single and multi-period problems

In traditional facility layout design method, the facility layout is governed by the flow intensity between departments, which is the product flow quantity between departments. A facility layout design must maintain its efficiency over time while coping with the uncertainty in product demand. An error in the product demand assessment can render the layout inefficient with respect to material handling costs. Analytical models for the determination of the risk involved in a facility layout design are difficult to derive when the problem of size and complexity increases. This paper presents a simulation-based method for predicting the uncertainty associated with the layout. The validation of the simulation approach against analytical procedures is first detailed. The methodology for the simulation based approach is provided. Three scenarios of increasing complexity and size are also detailed. Results from case studies have shown that the procedure results in reduction of risk as high as 80%.

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.

In this era of globalization, product demand and product mix disparate frequently. In addition, entry of new product and deletion of existing product due to changing market scenarios make the manufacturing environment uncertain. In the uncertain manufacturing environment, a facility layout design must be capable to handle all these changes while keeping minimal material handling cost (MHC) and re-configuration cost. This paper proposed a novel modified simulated annealing (modified SA) approach to solving bi-objective robust stochastic cellular facility layout problem (RSCFLP). The RSCFLP minimizes material handling distance (MHD) and thus MHC and maximizes similarity score for multi-periods and provides a robust layout design considering stochastic demand for multi-periods. The proposed robust layout design suits for all time periods and avoids re-configuration cost. The proposed modified SA is tested using twenty-five data sets with a varying number of machines, products, cells, time periods, and product demand. Lastly, results are compared to show the significance of proposed approach.

This paper focuses on facility layout design problem in microfluidic device manufacturing. Microfluidics device manufacturing requires exquisite work of operators and relatively much higher material cost than other types of manufacturing. Facility layout problem can directly affect the overall cost of manufacturing, particularly in handling and transport cost. Therefore, the objective of this study is to minimize the total handling and transport cost for facility layout design problem. A genetic algorithm (GA) is employed to find a good alternative facility layout design which is based on the performance metrics. Experimental results show that this approach is more feasible in dealing with the facility layout in microfluidics device fabrication.

ABSTRACTIn manufacturing industries, the facility layout design is a very important task, as it is concerned with the overall manufacturing cost and profit of the industry. The facility layout problem (FLP) is solved by arranging the departments or facilities of known dimensions on the available floor space. The objective of this article is to implement the firefly algorithm (FA) for solving unequal-area, fixed-shape FLPs and optimizing the costs of total material handling and transportation between the facilities. The FA is a nature-inspired algorithm and can be used for combinatorial optimization problems. Benchmark problems from the previous literature are solved using the FA. To check its effectiveness, it is implemented to solve large-sized FLPs. Computational results obtained using the FA show that the algorithm is less time consuming and the total layout costs for FLPs are better than the best results achieved so far.

The facility layout design has been regarded as the key to improve plant productivity, which are relevant to both manufacturing and service sectors. Facility Layout Problems (FLPs) are known to be NP-hard problems; various optimization approaches for small problems and heuristic approaches for the larger problems have been proposed to elucidate the problem. A mathematical model is developed for the unequal size facility layout problem with fixed flow between departments. We are considering the orientations of the departments with various sizes and aims to minimize the distance traveled by people, material, and other supporting services in the safest and most effective manner. Some of the constraints considered in the modeling are the restricted areas, reserved departmentry locations, and also the irregularity of the shapes of manufacturing layout. This paper focuses on the mathematical model and the solution of the non-quadratic assignment problem (non-QAP) by hybridizing the meta-heuristic methods i.e. Genetic Algorithm (GA) and Simulated Annealing (SA). This work could be used in future as a reference for those researchers interested in tackling this challenging unequal facility layout problem.

A well-planned arrangement of manufacturing departments on a two-dimensional planar region considerably increases the efficiency of its production systems, which is termed facility layout problem (FLP). Conventional layout design approach often designs intercell layout (determining exact location of each department on shop floor area) and flow path layout design of material handling system (MHS) step by step in a sequential manner. This results in suboptimal solutions for FLP. In this paper, an integrated approach is adopted to design the intercell layout and the flow path layout of MHS simultaneously. The quality of the final layout is evaluated by minimizing total material handling cost. Sequence pair (SP) representation is used for layout encoding. The translation from SP to layout is efficiently made by longest common subsequence (LCS) methodology. An elitist strategy genetic algorithm using simulated annealing (E-GASAA) as a local search mechanism is developed and tested with four test problem instances available in the literature. Elitist strategy is incorporated to enhance convergence characteristic of the proposed algorithm. It is found that the proposed E-GASAA is able to produce best solutions consistently for the test problem instance of different sizes within acceptable computational effort. In addition to that, we tried to reduce the computational load with the help of adopted LCS computation methodology and achieved a good improvement.

Solutions for the constrained dynamic facility layout problem

Facility layout design problem considers the departments’ physcial layout design with area requirements in some restrictions such as material handling costs, remoteness and distance requests. Briefly, facility layout problem related to optimization of the layout costs and working conditions. This paper proposes a new multi objective simulated annealing algorithm for solving of the unequal area in layout design. Using of the different objective weights are generated with entropy approach and used in the alternative layout design. Multi objective function takes into the objective function and constraints. The suggested heuristic algorithm used the multi-objective parameters for initialization. Then prefered the entropy approach determines the weight of the objective functions. After the suggested improved simulated annealing approach applied to whole developed model. A multi-objective simulated annealing algorithm is implemented to increase the diversity and reduce the chance of getting layout conditions in local optima.

The Facility Layout Problem (FLP) is a renowned and extensively researched problem that has attracted significant focus from various areas, including industry and manufacturing. One of the recent studies includes the examination of FLP issues in a large room. Analysing the layout of amenities and temperature controls in spacious areas like libraries is crucial for understanding how they affect people’s thermal comfort and energy consumption. The arrangement of facilities typically impacts the air distribution within a large room. Improper facility layout design might create indoor temperature disparities, with specific zones feeling excessively warm or chilly. Consequently, users are unevenly distributed due to each individual’s differing thermal comfort needs. Previous researchers have discussed this issue. However, after a detailed examination of previous studies, a few drawbacks have been identified in building mathematical models. These drawbacks include poorly organised mathematical modelling, ambiguous or disorganised data collection and analysis techniques, and the absence or ambiguity of variables and constraints. Therefore, this study proposed a structured mathematical approach to build a more efficient, inclusive, and reliable model. This study used a university library in Malaysia as a case study. A well-established and widely practised method for assessing mathematical modelling competency based on previous research has been adopted. Subsequently, the list of sub-competencies associated with the modelling process is utilised as a reference point for constructing a mathematical model in this research endeavour. As a result, the entire process of constructing a mathematical model is detailed, and recommendations for future enhancements are provided. This project is considered a significant advancement in the pursuit of conducting further FLP investigations in large rooms for the greater good in the future, which is part of the PhD research carried out at UUM.

Cellular manufacturing is a lean manufacturing approach that involves grouping machines, processes, and workstations into self-contained cells to reduce material handling, waiting times, and inventory. The layout design of cellular manufacturing facilities has a significant impact on their efficiency, productivity, and throughput. However, traditional trial-and-error methods for facility layout design can be time-consuming, costly, and risky. Digital twin simulation offers a powerful alternative by allowing designers to create virtual models of the facility and test different layout configurations before physically implementing them. Our study shows that digital twin simulation can help identify the optimal layout design that maximizes productivity, minimizes waste, and ensures the smooth flow of materials and products. Additionally, it enables us to evaluate the impact of changes in the production system on the facility's performance, helping decision-makers make informed decisions. Overall, this paper highlights the potential of digital twin simulations as a powerful tool for optimizing cellular manufacturing facility layout design and improving operational performance.

The research focus is redesigning the facility layout of Piedmont Plywood Industry, Port Harcourt, Rivers State, Nigeria. Optimal approach to productivity and cost to yielding in facility layout design modifications is the trend in this research work. The facility layout modification central idea is the plant layout factor. Plant layout factor deals path modification. That is arrangement of machine, equipment and work stations as close as possible for optimal utilization of available space in the work environment. The productivity index for the current layout or the existing layout is 0.000275m3/Naira. The Alternative 1 modification productivity index is 0.000289m3/Naira and that of Alternative 2 modification is 0.000296m3/Naira. This is an indication of higher rate of return on investment for the two alternative layout modifications. It is interesting to note that the results of the productivity index impacts positively on labor and capital cost of investment in such manner that there is tremendous cut back. The Alternative 1 modification resulted in total cost savings of N1,015,411.00/month while that of Alternative 2 is N1,436,545.00/month. These constitutes tremendous cut back on investments when accumulated over years. The Piedmont Plywood Product Industry and other wood product industries are strongly advised to inject the findings of the alternative layout modifications in the existing factory layout designs.

Freight villages reflect a modern way of organizing logistics, transport, and goods distribution activities. Warehouses are a basic element in such building complexes, and their efficient planning and operation is essential for the viability of the system. Warehouse design requires a mixture of analytical skills and creativity. Although effort has been dedicated to defining a global methodological design framework, the most scientific papers on the subject address well-defined, isolated problems. A practitioner may notice, however, that many warehouses offering efficient, cost-effective services are in operation and that several warehouse design manuals exist that tackle aspects of design and operation. Investigating academic and pragmatic points of view, this paper is an attempt to present an overall view of the facility layout and warehouse design problem, and it introduces the analysis and results of the preliminary design phase of a new freight village where issues related to facilities layout, warehouse sizing, and rail connections have been considered.

The selection of capital projects in a production environment is complicated by the existence of multiple and conflicting goals. Typical production objectives for cost minimization often conflict with goals for quality, environmental standards, labor relations, etc. This problem of project selection is further complicated by the uncertainty inherent in product demand, the key factor in production management. This paper approaches these complications by employing an integer goal programming (to compensate for multiple conflicting objectives) with chance-constrained capabilities (to reflect uncertainty in product demand). The approach is demonstrated via an in-depth case example of a production problem.

Facility Layout Problem (FLP) can be considered as a classical problem in quantitative studies. However, the literature in FLP are largely neglected the thermal comfort as part of the objective function. Today, energy savings for buildings are a major concern in the world as they cover a big portion of energy use. The public room consumes high energy use because of its ability to occupy many people at one time. Issues arise when each person has a dissimilar thermal satisfaction rate, while each area in a room provides a different temperature. There are many factors that influence the people dispersion in the room including the facility layout. However, it is really testing to handle an air-conditioning control () system by considering the mention factors to ensure the thermal satisfaction is increased and energy is reduced. Since lack of report on thermal factors in Facility Layout Problem (FLP) area, this work aims to optimize the temperature setting of an system at the best point and achieving the finest plan for the facility layout in a room. Further, our ultimate goals to maximize the thermal comfort level and reduce energy consumption are able to accomplish. A non-linear mathematical model is utilized to optimize the thermal satisfaction rate () and room layout. At the end of the article, we proposed an Evolutionary Algorithm (EA) to find a quality solution or near optimal since it is hard to solve this problem in a reasonable time.