Develop a software module carrying out production scheduling taking into account the specific constraints of a high precision metal parts machining workshop
In this project, a software module carrying out production scheduling and taking into account the specific constraints of a high precision metal parts machining workshop is developed. Features of industrial equipment make it possible to dramatically increase the utilization rate of equipment by pre-assigning tools to machines before the scheduling is carried out.
The machining of high precision metal parts is of great importance to Canada. This activity supports other high-tech industries such as the aeronautics sector. Although this activity makes use of very complex technological equipment (which is expensive to operate), the management of production activities (e.g. planning and scheduling of production) rarely involves the use of algorithms that could in fact optimize productivity.
Due to the lack of appropriate software tools, decisions are made manually resulting in a suboptimal use of resources. Although this seems to be a classic job shop scheduling problem, classical approaches do not apply well in this specific context.
In this project, a software module carrying out production scheduling is being developed which takes into account the specific constraints of a high precision metal parts machining workshop. Characteristics of industrial equipment make it possible to considerably increase the rate of use of equipment by pre-allocating tools to machines before carrying out the scheduling, rather than the reverse as is generally recommended in classic models.
To do this, two sub-optimization problems were addressed: (1) the assignment of tools to the turrets of numerically controlled machines, and (2) the scheduling of products/parts to be manufactured and their assignment to the machines.
IID Principal Investigators of this project
Jonathan Gaudreault Research Thrust 1 – Physical Environment
Université Laval Director, CRISI (Research Consortium for Industry 4.0 Systems Engineering)
Faculty of Science and Engineering
Department of Computer Science and Software Engineering
Director, CRISI (Research Consortium for Industry 4.0 Systems Engineering)
Industry 4.0 Internet of Things Logistics Machine Learning Operations Research
Claude-Guy Quimper, Jonathan Gaudreault, Marc-André Ménard (Université Laval)
Project Funding: 2017-2022
Let’s keep in touch!
Would you like to be informed about IID news and activities? Subscribe now to our monthly newsletter.