An Intelligent Supply Chain Planning and Execution Environment, Jens Pohl, May 2011 IS11-Pohl-Focus-Paper
An Intelligent Supply Chain Planning and Execution Environment
Jens Pohl,
PhD
Executive Director, Collaborative Agent Design Research Center (CADRC)
Director, KML Center (Scott AFB, Illinois)
California Polytechnic State University (Cal Poly), San Luis Obispo, California
Abstract
Logistic planning and execution processes in a supply-chain are subject to a high level of
complexity because of the number of parties and issues involved, the number of relationships
that exist among them, and the dynamic nature of the execution environment. The large volume
of data flowing through a sizable computer-based logistic planning and execution management
environment that is based on rote data-processing principles tends to overwhelm the human
users. As a result many opportunities for improving the efficiency of supply-chain processes and
thereby reducing costs are overlooked by the human users, who are forced into a reactive mode.
Similar data deluge symptoms are being experienced in other domains such as Internet searches
where the number of website hits returned for a single query can easily exceed several million.
The data deluge problem could be overcome if the context of the query could be defined by the
user and executed by the search engine in a context-based manner. This would require the
representation of a virtual model of real world context in the search software. The same need for
the representation of context in software exists also in the cyber security domain where data
encryption must be supplemented by the profiling of users and the continuous monitoring and
automated interpretation of network behavior.
This paper discusses the design concepts and implementation principles, and describes the end-
state capabilities of a computer-based intelligent logistic planning and execution environment
that includes a virtual model of real world supply-chain context and multiple agent groups that
are able to interact with each other and the human users. Implemented in a service-oriented
architecture (SOA) based infrastructure, the virtual context model provided by a multi-layer
ontology and the collaborative agents are able to continuously monitor the state of the supply-
chain by interpreting the flow of data in the appropriate context. This allows the agents to rapidly
re-plan in case of supply-chain interruptions, discover and act on opportunities for
improvements, and identify patterns and trends based on the continuous analysis of historical
data. As a result the human users are relieved from lower level data interpretation tasks and
provided with actionable information for reactive and proactive planning and execution
management functions. The author suggests that order of magnitude improvements in efficiency
and reduction in cost are achievable with context-based information-centric software systems.
1. Supply-Chain and Logistics
Organizations exist for some purpose and in virtually all cases this purpose involves the creation
and delivery of products, in the form of goods and/or services. To achieve its purpose the
organization uses a variety of resources such as people, information, materials and/or
components, and money, to perform operations that result in the delivery of products to its
customers. The required operations may include any number of activities such as manufacture,
transportation, training, serving, and selling, and typically involve many activities and
relationships that need to be coordinated within a network of interacting entities. The Chartered
Institute of Logistics and Transport (1998) defines supply-chain and logistics as follows:
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