Session: DAC-05-01-Decision Making in Engineering Design

Paper Number: 90836

90836 - An Information-Decision Framework to Support Cooperative Decision Making in the Top-Down Design of Cyber-Physical Manufacturing Systems 

Decision-making in the design of cyber-physical manufacturing (CPM) systems is complex due to many decisional entities and their complex interactions that need to be appropriately modeled and analyzed.

One approach to designing these systems is the goal-oriented inverse design (GoID), using which satisficing design solutions are sought in a top-down manner. In this approach, entity decisions are directed towards meeting the goals propagated inversely from the subsequent entity in the manufacturing sequence. However, achieving the goals in a top-down manner may not be feasible for certain scenarios due to the defined constraints, available bounds, and targets for an entity. This leads to design conflicts between the entities and loss in entity and overall system-level performances.

In this paper, we propose an information-decision framework that allows designers to model entity decision-making in a goal-directed manner, detect potential conflicts between entities, and regulate entity-level decisions to achieve improved entity and system-level performances. The regulation of entity decisions is accomplished by modifying active design variable bounds (considering the sensitivity of the goals to design variables), active constraint limits, or both jointly. The efficacy of the proposed framework is tested using a hot rod rolling problem involving sequential decisions. Using the problem, we showcase the use of the framework in detecting and systematically managing conflicts while designing the material, product, and manufacturing processes involved. The framework is generic, facilitates the top-down sequential design of interacting entities, and promotes cooperative design decision-making to manage design conflicts.

Presenting Author: Mathew Baby Florida Institute of Technology

Presenting Author Biography: Mathew Baby is a Ph.D. student in Mechanical Engineering at the Systems Realization Laboratory, Florida Institute of Technology working with Dr. Anand Balu Nellippallil. He holds a bachelor’s and master’s degree in Production Engineering and worked as an Assistant Professor in India for 8 years. His areas of research interest include Decision Support in the Design of Engineered Systems, Self-Organizing Systems, System Simulation & Modeling, and Supply Chain & Logistics Management.

Authors:

Mathew Baby Florida Institute of Technology
Anand Balu Nellippallil Florida Institute of Technology