Feed-Forward Control Systems
Where the goal is quality at every step

A primary objective of manufacturing is to convert raw materials into products. We think of this as a flow of materials through, in most cases, multiple operations or stages. This flow of materials is also accompanied by a flow of cost. That is, as materials move through various transformations, costs accumulate.

We think of an efficient manufacturing operation as one that minimizes non-value-add operations: Transportation, storage and inspection activities. An ideal flow material would be one that has only value-add operations, that is actual chip-cutting, parts mating, and so on. A necessary third flow, in order to optimize value-add activities, is a need to optimum information flow. This third flow can be defined as effective management – planning and controlling operations.

Our nation’s business schools have done, in my view, a great job over the last 50 years in developing effective strategic planning systems. We know a great deal about the technology of planning. On the other hand, I think these same schools have failed miserably is in the area of control theory. While most theories in business systems rely on feedback systems, very few, if any, have done research in the well-known technology for feed-forward control systems.

Feed-forward theory
Before we can explain the theory of feed-forward, we first need to understand manufacturing as a system. That is, manufacturing has inputs, transformations and outputs. This can be visualized as raw materials moving into a system, going through various transformations, and finally, ending as a product. Given this definition of a system, the second concept we need to understand about any systems is that unwanted disturbances enter system transformation activities. These disturbances generally cause deviations from product specification standards. The job of optimum information flow is to control these disturbances.

The ideal state would be one in which control devices, through various detections, identify potential disturbances and prevent them from entering the system. These devices work kind of like a personal computer virus detector.

We could for example, train a person to identify potentially damaging disturbances and prevent them from entering a system. In this situation, as a disturbance enters a process the operator observes an indication of the nature of the disturbance and, based on the entering disturbance, he/she adjusts conditions in such a manner as to prevent any ultimate change or variation in the controlled variable, product specifications.

Lean manufacturing theory
Toyota Motor Manufacturing Company utilizes very effective feed-forward control systems to prevent defects. This is sometimes known as “quality at the source.” Quality-at-the-source is achieved through various methods: Self-inspection, successive inspection, and “mistake-proof” devices. Generally, the primary detector is a person – the operator. An operator inspects the material when he receives it. Then he performs his operation. Next he inspects his/her work before passing it on. The next successive operator in the series performs the same series of inspections and so on.

Finally, and ideally, devices are used at the operator level to prevent operator mistakes. All these methods fit the description of feed-forward methods. These methods are given various names but what they actually do is perform feed-forward control.

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