Institute for Systems Research Technical Reports

As an example, in this paper we describe the techniques for manufacturing-operation planning used in IMACS (Interactive Manufacturability Analysis and Critiquing System). We compare and contrast them with the techniques used in classical AI planning systems, and point out that some of the techniques used in IMACS may also be useful in other kinds of planning problems.

Evaluating the manufacturability of a proposed design involves determining whether or not it is manufacturable with a given set of manufacturing operations - and if so, then finding the associated manufacturing efficiency. Since there can be several different ways to manufacture a proposed design, this requires us to consider different ways to manufacture it, in order to determine which one best meets the design and manufacturing objectives.

The first step in our approach is to identify all machining operations which can potentially be used to create the given design. Using these operations, we generate different operation plans for machining the part. Each time we generate a new operation plan, we examine whether it can produce the desired shape and tolerances, and calculate its manufacturability rating. If no operation plan can be found that is capable of producing the design, then the given design is considered unmachinable; otherwise, the manufacturability rating for the design is the rating of the best operation plan.

We anticipate that by providing feedback about possible problems with the design, this work will help in speeding up the evaluation of new product designs in order to decide how or whether to manufacture them. Such a capability will be useful in responding quickly to changing demands and opportunities in the marketplace.

Evaluating manufacturability involves finding a way to manufacture the proposed design, and estimating the associated production cost and quality. However, there often can be several different ways to manufacture a proposed design - so to evaluate the manufacturability of the proposed design, we need to consider different ways to manufacture it, and determine which one best meets the manufacturing objectives.

In this paper we describe a methodology for systematically generating and evaluating alternative operation plans. As a first step, we identify all machining operations which can potentially be used to create the given design. Using these operations, we generate different operation plans for machining the part. Each time we generate a new operation plan, we assign it a manufacturability rating. The manufacturability rating for the design is the rating of the best operation plan.

We anticipate that by providing feedback about possible problems with the design, this work will be useful in providing a way to speed up the evaluation of new product designs in order to decide how or whether to manufacture them.

In this paper we present the following results: 1. We give general mathematical definitions of machining features and FBMs.

2. We present a systematic way to generate the alternative FBMs for a part, given an initial FBM for the part.

3. For each FBM, interactions among the features will impose precedence constraints on the possible orderings in which these features can be machined. We show how to generate these precedence constraints automatically for each interpretation.

4. We show how to organize the above precedence constraints into a time-order graph that represents all feasible orderings in which the features can be machined, and examine the time-order graph to see if it is consistent. If it is not consistent, then there is no way to machine this particular interpretation.

This work represents a step toward our overall approach of developing ways for automatically generating the alternative ways in which a part can be machined, and evaluating them to see how well they can do at creating the desired part. We anticipate that the information provided by this analysis will be useful both for process planning and concurrent design.