Collaboration formalism for supply decisions networks
Abstract
Manufacturing and supply strategies have evolved from the notion of mass production focusing on economies of scale, to flexible production systems seeking economies of scope, to the concept of enterprise and supply networks aiming for economies of collaboration. The emergence of supply networks poses new challenges derived from a growing complexity in coordinating the flow of materials and information within and among an increasing number of network participants. Latest developments in collaborative control theory emerge as a promising solution but need further theoretical formulation to tackle complex decision networks problems. This dissertation addresses the problems of collaboration among multiple decision makers in large supply networks. Five new dimensions of collaborative control theory (the strategic, physical, economic, chemical, and inter-organizational dimensions) are introduced to guide the correct design of supply decisions networks. Inspired in the proposed framework, two dimensional optimization algorithms (the constrained-collaboration optimization, and the parallel, reconfigurable, inter-organizational optimization algorithms) and two dimensional assessment protocols (the service-cost negotiation and value of collaboration protocols) are developed to support collaborative supply and distribution decisions. The newly developed approach is illustrated by three case studies from a global industry network (collaborative physical distribution planning, direct/indirect delivery decisions, and decentralized decisions in a parallel, reconfigurable, inter-organizational network), demonstrating its advantages. Compared to current practices in industry, the results from the three case studies, indicate the proposed collaboration formalism offers significant improvements in several performance indicators, such as: 100% improvement in direct delivery ratio, 55% increase in resources utilization, 25% to 40% improvement in total time-to-serve, and 20% reduction in the total physical distribution cost.
Degree
Ph.D.
Advisors
Nof, Purdue University.
Subject Area
Industrial engineering
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