Walter W. Buchanan

Regulating Bullwhip Effect in Supply Chains through Modern Control Theory

Modeling and control of supply chain management (SCM) systems are still problematic today even though we have relatively powerful methods and IT tools available at our disposal. The complexity and the multi-disciplinary nature of the problem attracted the attention of many researchers from various different disciplines. It is possible to classify the available approaches to supply chain management as ad-hocacy, what-if-simulation, control theory, filter theory, and operations research theory. The studies that are based on control theoretic approach are limited to what is known as classical control theory; the modeling and control study presented in this work is based on the so called modern control theory. As far as the authors know, this is the first study of its kind. Through the use of modern control theory, the limitations that are imposed by its classical counterpart can be overcome, providing the opportunity to extend the modeling and control work to non-linear, time-varying, stochastic, adaptive, and large-scale systems, effectively. In the present study, a supply chain system is modeled through state-space techniques; the model is linear, discrete-time, and stochastic. The model is then analyzed to study the stability, controllability, and observability properties of the system, which are vitally important in control system design. Finally, a linear quadratic Gaussian (LQG) controller is designed with the aim of regulating the bullwhip effect in the system. The initial analyses suggest that the controller structure developed is well equipped to regulate the bullwhip effect in a supply chain system effectively.

A model for assessing the effect of new technologies on production

The model presented in this study has been adopted from the control engineering field. Its purpose is to allow system designers or engineers to view a complex production process in an abstract and a compact form so that they can easily assess the effect of introducing new technologies and organizational forms into production.

ON PEDAGOGICAL CONCERNS OF ENGINEERING COURSES IN DISTANCE LEARNING ENVIRONMENTS

The objective of this study was to use mentalmaps to analyze the design of higher education students ontheir understanding of technology. The courses wereworked: Computer Science, Technology Systems for InternetTechnology in Computer Networks and Technology Analysisand Systems Development, in particular, was working thirdyearstudents of the Course of Computer Science andstudents of the early years of technological courses. Just asscience, technology is evolving more and more, bothevolving categories irreversible, we must haveunderstandably o of its strengths and weaknesses in society,so we have to think and understand the movement CTS.Index Terms ⎯ mental maps, uniformity and education.

Joint cognitive system design and process control

The aim in this paper is to look at some important issues involved in the design of human-machine systems for process control and automation, and discuss the significance of Joint Cognitive Systems (JCS) paradigm in the design process. The discussion is presented within the framework of Cognitive Systems Engineering (CSE) in particular, and in Socio-Technical System (STS) design framework, in general. The discussion is focused on process control problems in process and manufacturing industries. As a relatively new paradigm in human-machine system design, the potential benefits offered by the JCS will be elaborated. Also, a comparative view of Design for Simplicity and Design for Complexity is provided as two alternative approaches in the JCS paradigm in relation to process control and automation. The use of decision support systems in JCS design will also be discussed briefly.

Quantitative Modeling of Dynamic Processes for Systems Development: A Review

The aim in this paper is to review some of the approaches available for developing quantitative models of dynamic processes in system development. The review is performed through a systems engineering perspective with the intension of guiding systems engineering students and practitioners in the modeling process. The major conclusion drawn from the study is that some formal approaches to hierarchical system modeling should receive more attention in the treatment of the subject matter