Combining optimisation and simulation for steel production scheduling

Abstract

Purpose -Scheduling problems in steel plants tend to be difficult and require complex algorithms due to many constraints. An approach is presented where only the main constraints are included in the scheduling algorithm. The schedule is validated using a discrete-event simulation model that includes additional detail. Design/methodology/approach -The combined approach is utilised for production scheduling in a steel mill in Finland. Operational performance of the steel mill is measured before and after software installation. The paper presents the scheduling environment, the software application and the resulting increase of production. Findings -Case experiences indicate that combining optimisation techniques with simulation is beneficial. The optimisation can be kept simpler as validation with a simulation model increases the credibility and accuracy of the resulting schedule. During software development and testing, the simulation model offered a testing environment for the optimisation algorithm. Practical implications -The case implementation was a success that increased production without making trade-offs with other production goals. Company management estimate the productivity increase directly caused by the project to be worth e2,500,000 annually. Originality/value -The paper presents a successful application of simulation for schedule validation in a complex and demanding environment.

User-centric development of simulation based manufacturing operation planning and scheduling system

“…There are also many dedicated software packages like Preactor (www.preactor.com), Asprova (www.asprova.com), and others made by simulation engineering offices, like Simul8-Planner (www.simul8-planner.com) and Delfoi Planner (www.delfoi.com/web/en_GB/) available. There are also studies [9] on how to combine simulation and optimization for scheduling.…”

Investment analysis of an integrated industrial park with carbon capture

“…A presentation of models that specifically address economics of the raw materials in steel plants can be found in Westerberg et al (1977) and Gao and Tang (2003). Scheduling and strategic planning of steel production are dealt with in Appelqvist and Lehtonen (2003) and Bielefeld et al (1986). Optimisation models of Natural gas power plants are presented in Makkonen andLahdelma (2006), Ferrari-Trecate et al (2002) and Yokoyama and Ito (2006).…”

Data Analytics in Master Cam Setup Sheet for Improved Manufacturing

“…It is 2D CAM system having CAD tools which enables user to design Computer generated parts on a desktop and also guides CNC tools for manufacturing of parts. Eventually 2D CAM system was modified to 3D system as per need of time [1].…”