Lot streaming optimisation of scheduling problems in open-shop manufacturing environments
Scheduling manufacturing operations is vital for companies to thrive under high competition in various manufacturing industries. The production scheduling process allocates resources such as time for each specific operation, detects possible conflicts of allocated resources, controls job release timings on the shop floor, ensures delivery due dates, and thus increases the productivity and efficiency of the workforce. In this paper, a method usually exploited to reduce the production duration, dubbed 'lot streaming', is adapted and applied to solve scheduling problems in open shop environments. A new integer linear programming (ILP) model is developed to outline the integration of lot streaming scheduling and constraints of partial functionality machines in an open shop environment to minimise the makespan. In such an environment, there are no restrictions on the order in which the machines perform the job's operations. The developed model is applied and tested on five different hypothetical problems. The experimental results are presented, and the efficiency of the proposed ILP is discussed. It is concluded that considerable reductions in the makespan can be achieved with the inclusion of lot streaming in an open shop production environment.
Authors
- Ammar Al‐Bazi (ORCID: https://orcid.org/0000-0002-5057-4171)
- Mohammad A. Shbool (ORCID: https://orcid.org/0000-0002-9413-7985)
- Anees Abu Monshar
- Mahmood Ahmad (ORCID: https://orcid.org/0000-0002-9974-0150)
- Rami Hikmat Al Hadeethi
- AbdulSattar Al Alusi
Institutions
- University of Jordan (JO)
- Aston University (GB)
- Manufacturing Technology Centre (United Kingdom) (GB)
- American University in the Emirates (AE)
Publication Details
- Journal
- International Journal of Industrial and Systems Engineering
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1504/ijise.2025.148891
- Primary Topic
- Advanced Manufacturing and Logistics Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00