Shadi Keshavarzmanesh

A function block based approach for increasing adaptability of assembly planning and control

Todays market turbulences cause frequent changes in manufacturing environments. Products diversity, small batch sizes and short life cycles have increased production uncertainties and created a highly dynamic shop floor environment. One essential requirement of such an environment is an adaptive planning and control system that is sufficiently agile to respond to the variety of production requirements and enable easy system reconfiguration at run-time. When developing a product, assembly is a key area that impacts the manufacturing systems responsiveness to the changes. In this research, a framework and a new methodology are introduced to increase the adaptability and autonomy of job-shop assembly process planning and control using function blocks (FBs). A function block is a reusable functional module with an explicit event-driven model, and provides for data flow and finite state automata based control. Event-driven and FB-enabled decision-making is unique in adaptive assembly planning and control. It is explained through an example of a two-robot assembly work cell, where the result of the adaptive planning is wrapped in FBs for execution. The proposed approach has been implemented and simulated using Matlab Simulink in the case study. The simulation demonstrates how this approach would increase the adaptability and responsiveness to changes that may occur regularly in dynamic job-shop assembly operations.

Design and simulation of an adaptive and collaborative assembly cell

Nowadays, product-mix in small batches contributes to shop floor uncertainties, whereas distributed resources are handled collaboratively during assembly planning. There is a growing need to develop methods that can increase adaptability and flexibility in dynamic and collaborative job-shop assembly floors. Based on our previous work on an assembly planning framework using Function Blocks (FBs), a novel approach to assembly planning and control is developed, which enables adaptive decision making besides effective plan execution. Following our previous work, this paper reports the latest development of design and simulation of an FB communication network in Matlab-Simulink environment, and validates the methodology through an example.

Reconfigurable Facility Layout Design for Job-Shop Assembly Operations

Highly turbulent environment of dynamic job-shop operations affects shop-floor layout as well as manufacturing operations. Due to the dynamic nature of layout changes, essential requirements such as adaptability and responsiveness to the changes need to be considered in addition to the cost issues of material handling and machine relocation when reconfiguring a shop floor’s layout. Here, based on the source of uncertainty, the shop-floor layout problem is split into two sub-problems and dealt with by two modules: re-layout and find-route. Genetic algorithm is used where changes cause the entire shop re-layout, while function blocks are utilised to find the best sequence of robots for the new conditions within the existing layout. This chapter reports the latest development to the authors’ previous work.