The Fourth Industrial Revolution (Industry 4.0), with the help of cyber-physical systems (CPS), the Internet of Things (IoT), and Artificial Intelligence (AI), is transforming the way industrial setups are designed. Recent literature has provided insight about large firms gaining benefits from Industry 4.0, but many of these benefits do not translate to SMEs. The agent-oriented smart factory (AOSF) framework provides a solution to help bridge the gap between Industry 4.0 frameworks and SME-oriented setups by providing a general and high-level supply chain (SC) framework and an associated agent-oriented storage and retrieval (AOSR)-based warehouse management strategy. This paper presents the extended heuristics of the AOSR algorithm and details how it improves the performance efficiency in an SME-oriented warehouse. A detailed discussion on the thorough validation via scenario-based experimentation and test cases explain how AOSR yielded 60–148% improved performance metrics in certain key areas of a warehouse.

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This is a summary of a report which has been reviewed in the Office of Civil Defense and approved for publication.Approval does not signify that the contents necessarily reflect the views and policies of the Office of Civil Defense.

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Our principal focus in this paper is on ways that a Fast Close process (or indeed any reserving process) can be structured to maximise the value added within the process given the time and resource available. This builds on the use of actual vs. expected techniques investigated in our previous paper, and also looks at forces external to the reserving function that may derail smooth progress. We highlight a number of practical ways that the balance can be restored in favour of adding value rather than crunching numbers. This paper forms the second in the TORP series.