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Supply Chain Digital Experts

Digital Experts

Next Step to Supply Chain Digitalization

With Gartner’s Stage 5 maturity model of the supply chain comes digitalization of the supply chain, what we refer to as the Digital Mirror© of your physical supply chain. Such an accurate digital model lends itself to autonomous operation using agents that can sense, interpret, respond and get better over time. We refer to these agents as “Digital Experts.” Much like any other expert they have an understanding of their environment, what is normal and what is an exception, and what needs to be done based on each event. Their decisions may change over time based on their ability to “learn” from their experiences.

Digital Experts have domain expertise in almost every aspect of supply chain operation. Examples are supplier management, web monitoring, financial analysis, customer monitoring and delivery service amongst many others. A supplier Digital Agent is constantly monitoring the deliveries that are to be made ensuring that there are no delays; and if there is one then alerts are sent to appropriate agents, planning system, or a human for correction. In the meantime, remembers the event for future learning and possible patterns that might be emerging. In addition, it is monitoring suppliers’ lead-time performance whether it is changing over time or across seasons, it identifies single sourced parts as well as presence of substitute parts.

Agents can also be highly autonomous in performing tasks. Consider the task of job sequencing for Factory Scheduling. This agent, based on the given model sequences the jobs for each equipment and monitors the shop floor for events such as equipment breakdown, quality issues, maintenance times, tool availability etc. Based on each event it may decide to change the sequences across all or a subset of resources. As before, it also keeps track of the events and looks for patterns of behavior in resources and products as well as tools, setup time and so on. However, there comes a time no amount of sequencing can help in addressing the problem at hand, e.g. loss of power or breakdown of a major piece of equipment. Such events require a re-plan and possible reprioritization of all the orders to ensure better delivery performance. This is the time, when a higher level of intelligence in the form of a Factory Planner or Supply Chain Planner, or even a Network Optimizer needs to be invoked to address the problem.

The above modus operandi describes how Adexa’s unified data model functions and how continuous planning results based on real-time events from the operations or external sources such as new orders, factory disruptions, or even changes in the weather.

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