Abstract: Background: A facility layout problem (FLP) is an NP-complete (non-deterministic polynomial) problem, for which is hard to obtain an exact optimal solution. FLP has been widely studied in various limited spaces and workflows. For example, cafeterias with many types of equipment for troops cause chaotic processes when dining. Objective: This article tried to optimize the layout of a troops’ cafeteria and to improve the overall efficiency of the dining process. Methods: First, the original cafeteria layout design scheme was analyzed from an ergonomic perspective and two new design schemes were generated. Next, three facility layout models were designed, and further simulation was applied to compare the total time and density of troops between each scheme. Last, an experiment of the dining process with video observation and analysis verified the simulation results. Results: In a simulation, the dining time under the second new layout is shortened by 2.25% and 1.89% (p
Abstract: The dynamic facility layout problem is a really critical issue in the competitive industrial market; thus, solving this problem requires robust design and effective simulation systems. The sustainable simulation requires inputting reliable and accurate data into the system. So this paper describes an automated system integrated into the real environment to measure the duration of the material handling operations, collect the data in real-time, and determine the variances between the actual and estimated time schedule of the operations in order to update the simulation software and redesign the facility layout periodically. The automated method- time measurement system collects the real data through using Radio Frequency-Identification (RFID) and Internet of Things (IoT) technologies. Hence, attaching RFID- antenna reader and RFID tags enables the system to identify the location of the objects and gathering the time data. The real duration gathered will be manipulated by calculating the moving average duration of the material handling operations, choosing the shortest material handling path, and then updating the simulation software to redesign the facility layout accommodating with the shortest/real operation schedule. The periodic simulation in real-time is more sustainable and reliable than the simulation system relying on an analysis of historical data. The case study of this methodology is in cooperation with a workshop team for producing mechanical parts. Although there are some technical limitations, this methodology is promising, and it can be significantly useful in the redesigning of the manufacturing layout.
Abstract: Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.
Abstract: In this research, we have developed a new efficient
heuristic algorithm for the dynamic facility layout problem with
budget constraint (DFLPB). This heuristic algorithm combines two
mathematical programming methods such as discrete event
simulation and linear integer programming (IP) to obtain a near
optimum solution. In the proposed algorithm, the non-linear model
of the DFLP has been changed to a pure integer programming (PIP)
model. Then, the optimal solution of the PIP model has been used in
a simulation model that has been designed in a similar manner as the
DFLP for determining the probability of assigning a facility to a
location. After a sufficient number of runs, the simulation model
obtains near optimum solutions. Finally, to verify the performance of
the algorithm, several test problems have been solved. The results
show that the proposed algorithm is more efficient in terms of speed
and accuracy than other heuristic algorithms presented in previous
works found in the literature.
Abstract: This paper presents an algorithm which
combining ant colony optimization in the dynamic
programming for solving a dynamic facility layout problem.
The problem is separated into 2 phases, static and dynamic
phase. In static phase, ant colony optimization is used to find
the best ranked of layouts for each period. Then the dynamic
programming (DP) procedure is performed in the dynamic
phase to evaluate the layout set during multi-period planning
horizon. The proposed algorithm is tested over many
problems with size ranging from 9 to 49 departments, 2 and 4
periods. The experimental results show that the proposed
method is an alternative way for the plant layout designer to
determine the layouts during multi-period planning horizon.
Abstract: Facility Layout Problem (FLP) is one of the essential
problems of several types of manufacturing and service sector. It is
an optimization problem on which the main objective is to obtain the
efficient locations, arrangement and order of the facilities. In the
literature, there are numerous facility layout problem research
presented and have used meta-heuristic approaches to achieve
optimal facility layout design. This paper presented genetic algorithm
to solve facility layout problem; to minimize total cost function. The
performance of the proposed approach was verified and compared
using problems in the literature.