Optimisation of Machine Layout Using a Force Generated Graph Algorithm and Simulated Annealing

Abstract

This paper presents a novel heuristic method for machine layout optimisation, developed in the course of an internal factory logistics optimisation project. The method is developed from a force-directed graph drawing algorithm, and integrates random permutations using simulated annealing to avoid local minima. The method was verified and validated with a discrete event simulation (DES) model of a furniture development factory consisting of 140 machines. The DES model was developed for manufacturing system analysis as well as design and testing of optimisation methods. The main optimisation goal was reduction of transport costs by minimising the total distance the products travel between the machines. The optimisation problem extends the quadratic assignment problem (QAP) by allowing arbitrary granularity of locations, facility sizes and fixed facilities. The resulting method can be used to solve a wider range of problems by altering the optimisation function or adding new feasibility conditions.

Industry 4.0 and the New Simulation Modelling Paradigm

“…The attributes can contain several lines of programming code describing how the block operates in different situations and states. (Rodič & Kanduč, 2015) The developed Java application manipulates XML code to change data on machines and all other relevant abstract objects such as connectors, sources and sinks that are connected to the blocks of machines. Specifically, the Java application reads the blocks in the template file and copies them according to input data.…”

“…Products and carts play a role of transactions in DES and are therefore constructed dynamically during simulation. The resulting modelling and simulation system, shown in Figure 4 is composed of four main elements Figure 4: Schematics of a system implementing automated DES modelling (Rodič & Kanduč, 2015) Unauthenticated Download Date | 5/12/18 10:06 AM (Rodič & Kanduč, 2015):…”

“…Automated model building and modification however requires that the model structure can be modified with an algorithm without manual interventions. (Rodič & Kanduč, 2015) These three points summarize the main changes to the simulation and modelling paradigm in the change from stand-alone simulation-based decision support system to the Digital Twin:…”

“…Automated model building and modification however requires that the model structure can be modified with an algorithm, without manual interventions. (Rodič & Kanduč, 2015) Developing a static simulation model that would cover all possible (i.e. 30,000) products that may appear in client's orders is not realistic as it takes approximately 15 minutes to complete a model of a process for each product, and a model containing 30.000 process also exceeds the memory limitations of the modelling tool used (Anylogic, http://www.anylogic.com/).…”

“…The model and method were tested in the optimisation task: reduction of product travel distance through modifications of factory layout, using a novel heuristic optimisation method based on force directed graph drawing. (Rodič & Kanduč, 2015) …”