Production process planning, based on manufacturing knowledge and product design, provides the operation instruction to the shop floor and develops the list of necessary tooling, equipment, and facility requirements. Traditionally, process planning is carried out by experienced manufacturing professionals. It is particularly useful during the production start up. However, owing to the increasing attention drawn by mass customization, which leads to the increasing number of product varieties along with rapid introduction of new products, the traditional approach of process planning is no longer economical from the amount of labor invested in preparing them, but more importantly, it fails to utilize the flexibility of modern manufacturing systems and adapt to the changing environment in m...[ Read more ]

Production process planning, based on manufacturing knowledge and product design, provides the operation instruction to the shop floor and develops the list of necessary tooling, equipment, and facility requirements. Traditionally, process planning is carried out by experienced manufacturing professionals. It is particularly useful during the production start up. However, owing to the increasing attention drawn by mass customization, which leads to the increasing number of product varieties along with rapid introduction of new products, the traditional approach of process planning is no longer economical from the amount of labor invested in preparing them, but more importantly, it fails to utilize the flexibility of modern manufacturing systems and adapt to the changing environment in modern manufacturing.

With regard to this issue, this thesis attempts to propose an autopoietic approach to model assembly process planning which can generate plans based on the wide variety of product requirements with small batch and dynamically changing available resources. Maturana and Varela coined the word “Autopoiesis” which describes the nature of reproduction of living systems. They proposed the concept of distinction of organization and structure and redefine cognition, which in the context of Autopoiesis, refers to the capacity of compensating perturbations.

In our approach, production processes are represented as assembly capabilities of employees which are structural components of the system whereas, organization refers to the relationship of the components that can realize a process plan. By capturing the three autopoietic properties, namely self-organization, self-production and self-reference, capabilities are established in the form of process building blocks (PBBs) allowing dynamic assembly towards incoming requests/orders. Thus, process plans are generated by coordinating those process build blocks with respect to the incoming service requests.

Hence, with our approach, a higher degree of flexibility can be achieved as plans are assembled case by case according to both the environment and past experience. Learning mechanism is implemented as well to enhance the performance of the coordination.