Abstract :
As was identified in the autonomic nervous system (ANS) analogy key points, an autonomic logistics (AL) approach must know what the optimal state of the system is and what constitutes an actionable deviation from that state. It must also know what to do to remedy that situation. The analysis approach presented will acquire the data to establish the optimal state. A mechanism to monitor and continuously refine the optimal state can then be developed. Like the ANS system, AL is ultimately a reactive system, the key is to strategically and systematically develop a suitable reaction management approach that minimizes system mission or performance risk. The analysis clearly defines the system limitation, expectations, and tolerance constraints. This results in implementation of supportable equipment, processes, and procedures that are better suited to achieve and sustain the desired level of mission success
Keywords :
decision making; logistics data processing; risk management; tolerance analysis; ANS analogy; actionable deviation; analysis approach; autonomic logistics; autonomic nervous system; optimal state; performance risk; reaction management; reactive system; system expectations; system limitation; system mission; tolerance constraints; Biological control systems; Control systems; Decision making; Humans; Logistics; Negative feedback; Nervous system; Procurement; Transportation; Weapons;
