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Using Detailed Data in Productive and Green Operations

david dornfeldShow me some numbers!

At the end of my last article, I said that it is necessary to address green manufacturing and the role of digital enterprises in the context of informing the customers each enterprise serves as well as those to whom the enterprise appears as the customer. Importantly, this has to be done both external to the organization as well as inside. What does that mean? With apologies to again referring to articles… this starts with the Google earth view of manufacturing. This was first introduced in an article way back in 2009. It bears refreshing everyone’s memory! The idea, shown in the image below, envisions one starting at the enterprise level and then zooming in to increasingly detailed parts of the manufacturing enterprise spanning

 “Google-earth” view of manufacturing
the facility, line or system in the facility, the machines in the line, the tooling on the machines and finally the process on the machine. This image is updated from the first one shown back in 2009. Along the left side of the image are characteristics of data flow and operations. For example, data rates and response rates of the elements at the different levels range from weeks and months at the highest level reflecting long term planning to minutes and hours in the line for organization of production to seconds and minutes in terms of the machine functions operation as in “macro planning” and then milliseconds and microseconds at the tooling process levels. These data rates reflect the speed of changes occurring in some aspect of the element that has importance to the overall functioning of that element and, necessarily, the consumption of resources.  The illustration below, from Vijayaraghavan and Dornfeld, D., “Automated Energy Monitoring of Machine Tools,” CIRP Annals, 59, 1, 2010, pp. 21-24) shows this temporal aspect of decisions and impact more clearly.
Required data rates at different levels of the manufacturing enterprise

To affect process control at the process level (here for a metal cutting operation – hence the reference to chips and cutting tool) one needs to have data and response at the micro/millisecond rate. As one moves higher in the structure the timing scale slows down proportionally. When reaching the enterprise level where supply chain management and asset management is of concern the decision and response time is longer. This is not, however, to imply that there are not decisions in supply chain management that do not occur more rapidly in some cases. In fact, the interesting thing about this type of representation is to look for the dependencies at lower levels on decisions and responses at higher levels. For example, a catastrophic tool failure at the process level that causes substantial down time and loss of availability of the machine and line could ripple up to the production planning and scheduling level if the disruption is substantial.

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