SCHEDULING OF FLEXIBLE MULTIPURPOSE
Systematic methods and tools for managing the complexity
Process Operation, Monitoring & Analysis (T4-2P)
Keywords: Flexible systems, Multipurpose scheduling
In a continuously changing and competitive environment, increasing productivity and quality is crucial for process and manufacturing industries. Significant improvements in technology have been achieved in recent years. One of the frequent solutions to low productivity and poor quality is automation1. Its application involves higher system flexibility, better operation control, reduction of manpower, and many other benefits. Therefore, the effective configuration and coordination of operations in automated lines and workstations play an important role not only in manufacturing but also in pharmaceutical and food industries. However, most of the situations studied so far do not consider the coexistence of information/constraints typical from the process industry (fluid management, recycles, capacity and time limitations, dependency on operating conditions,…) and information/constraints from the manufacturing or assembly industry (robotized tools, geometrical problems, …), and in many cases their interaction, which happens frequently in these industries.
In such circumstances, the paper focuses on the scheduling of flexible multipurpose back-up chemical/assembly processes in a fully robotized environment, whose main function is to replace labour in short series production and production peaks. The automated process consists of a set of robotized units and intermediate storages, where a set of assembly operations must be processed to obtain the final product. The main aim is to allocate the available resources to the assembly activities and determine the detailed sequencing and timing of operations so that makespan is minimized and resource use maximized.
A rigorous mathematical model is developed using mixed-integer linear programming. Technological constraints regarding process systems, product assembly, resources availability and different production scheduling goals are considered. The possible coordination of several automated processes and facilities in the plant is also taken into account.
Moreover, dynamic variables related to the production process, such as variable processing and transportation times, machine failure, machine repair times, raw material availability, and so on, can be considered as a two stage approach, where the simulation of different scenarios leads to eventually identify a robust schedule.
Finally, the schedule is also obtained using existing heuristic rules. The obtained models are tested in a case study from the chemical industry. Therefore, their performance is checked and results are compared.
Bibliography
1. Kaighobadi, M.; Venkatesh, K. Flexible Manufacturing Systems: An Overview. Int J of Op & Prod Man 1994, 4, 26-49.
See the full pdf manuscript of the abstract.
Presented Wednesday 19, 13:30 to 15:00, in session Process Operation, Monitoring & Analysis (T4-2P).
