We describe a general approach for dynamic and intelligent reconfiguration of real-time distributed control systems that utilizes the IEC 61499 function block model. This work is central to the development of distributed intelligent control systems that are inherently adaptable and dynamically reconfigurable. The approach that is used takes advantage of distributed artificial intelligence at the planning and control levels to achieve significantly shorter up-front commissioning times as well as significantly more responsiveness to change. This approach is based on object-oriented and agent-based methods, and aims at overcoming the difficulties associated with managing real-time reconfiguration of an intelligent manufacturing system.

Distributed intelligent control involves matching the control model more closely with the physical system. This is particularly relevant to industrial control systems that are required to control widely distributed devices in an environment that is prone to disruptions. Although considerable work has been conducted on the application of agent technology to the upper levels of manufacturing control (e.g., scheduling, planning, supply chain management, enterprise integration), the application of these techniques to the physical level of control where real-time constraints are prevalent is relatively new. This paper provides background on the work in this area, discusses key research themes in developing real-time distributed intelligent control systems for industrial applications, and concludes by sharing thoughts about the future prospects in this area.

Merges the latest results obtained by the holonic manufacturing systems (HMS) consortium with the latest developed standards for platform interoperability released by the Foundation for Intelligent Physical Agents (FIPA) to propose a novel e‐business model: the holonic e‐enterprise (HE). The HE extends both the HMS and FIPA models. On one side it extends the holonic manufacturing paradigm with one top level, the inter‐enterprise one. On the other side it extends the multi‐agent system (MAS) paradigm to the hardware (physical machine) level.

In the current research we examine the effects of a new team training system that can be readily integrated into post-secondary teaching and learning activities. Our training focuses on generating productive and constructive conflict by invoking an evidence-supported information sharing and decision-making concept known as constructive controversy. We used 517 student teams (1,659 students) organized into a no training comparison condition, a classroom-only training condition (partial training), and a classroom-plus-booster training condition involving conflict reflections (full training). We found that teams in the full training outperformed those in both the partial training and no training conditions in generating the most productive pattern of conflict (referred to as conflict profiles), and that patterns of conflict had implications for effective conflict management and team efficacy for innovation.