Data processing: generic control systems or specific application – Specific application – apparatus or process – Product assembly or manufacturing
Reexamination Certificate
1998-08-28
2002-07-02
Picard, Leo (Department: 2121)
Data processing: generic control systems or specific application
Specific application, apparatus or process
Product assembly or manufacturing
C700S106000, C709S241000
Reexamination Certificate
active
06415196
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates to the field of solutions to manufacturing-scheduling (MS) problems. More particularly, this invention relates to a new and improved MS process or program flow for solving finite capacity planning (FCP) problems in which the logic and data models used to derive the solution are generically applicable to a wide variety of different types of businesses, and as such, are highly flexible and adaptable to accommodate the individual circumstances associated with different businesses. Further still, the new and improved program flow of the present invention more effectively derives schedules or plans for solving MS problems by use of a more generic and expressive utilization of resources to execute a derived plan for solving the problem.
2. Description of Background Art
Scheduling the use of equipment and facilities to manufacture products has been a significant concern and problem in the field of manufacturing for almost as long as products have been manufactured. The best use of the facilities and equipment results in greater productivity and profit. The vast majority of MS problems have been resolved by humans without the aid of computing tools, particularly in businesses where the maximum use of the manufacturing equipment and facilities has not been essential to the success of the business.
The increasing size of businesses in general, coupled with increased competitive pressure, have magnified the difficulties of MS problems to the point where efficient human resolution of the issues posed has become impossible or at best inefficient. Consequently, MS software tools and processes have been developed to address these issues.
In general, however, existing MS software tools and processes are extremely complex to use and understand, and, in general, do not adapt conveniently to a variety of different businesses in an efficient way to address the particular issues associated with the individual business. Undoubtedly, the limited adaptability of prior MS software processes is simply further confirmation of the complexity of the MS problem. From a generic standpoint, the complexity of the MS problem results from the interaction of a relatively large number of factors necessary to create an adequate solution to the MS problem. The complexity of the MS software development process to accommodate the magnitude of issues involved, and the complexity of MS modeling of the business which is emulated by the software, have not permitted previous MS software processes to be as successful as expected. As a consequence, most prior MS software has required the business characteristics to fit a relatively fixed model, rather than to allow the individual business characteristics to form the model.
After a functional MS model has been developed, the developer is extremely reluctant to change that model in any significant manner. It is difficult and time-consuming to derive a new MS model or to make changes in a previous model. The complexity of a MS program is considerable, typically requiring tens or hundreds of thousands lines of software code. Writing an extensive amount of software code creates opportunities for numerous errors, thereby requiring extensive trial and error use to eliminate the unforeseen errors which are revealed from use. Therefore, writing additional code is not a desirable approach to solving individual MS problems.
This complexity exists despite the fact that many of the basic concepts involved in the MS model itself seem almost intuitive. Concepts which may appear intuitive in MS situations are usually accomplished in MS software only with considerable difficulty, effort and creativity.
Under the constraints of inflexible modeling, the individual characteristics of the business being modeled are made to fit the pre-existing MS model. Forcing the business to fit the model usually results in a less than satisfactory MS solution. Since the individual differences and aspects of a business can not be completely accommodated by the single, relatively-inflexible model, the resulting solutions are usually not complete. Users must still apply logic and intuition based on experience to further refine and apply solutions derived from the previous MS software processes. Furthermore, the human adjustment to the software-derived schedule or plan has made it difficult to track the use and application of the equipment and resources, and has made it very difficult to interrelate numerous schedules for manufacturing different products. Most sizable manufacturing businesses employ numerous schedules to maximize the effective use of their equipment and facilities. A partial solution obtained from a less effective MS software program does not adequately address the complete problems of a business, and may complicate an already highly complex problem.
Despite the difficulties encountered in solving MS problems with software, basic software concepts have evolved over the last three to four decades. The original MS processes were referred to as materials requirements planning (MRP). MRP is generally regarded as inadequate to meet current problems, primarily because MRP focused solely on the procedures for manufacturing a product, referred to as “routes,” and the timing associated with completion of the product.
The problem with MRP is that it assumed an infinite capacity for each of the resources (e.g., work stations, tools or people) available for use in the machining, assembly and production of the product. To manufacture a product there is a bill of materials which describes all of the components. MRP is good at exploding the bill of materials and working backwards from the completion date to schedule the production and acquisition of the materials on the bill to complete the project at the desired time. The problem is that MRP assumes an infinite capacity of resources. The assumption is not realistic. There are finite restrictions on resources in the real situation. The present invention solves these problems because it takes into consideration the practical and finite limits on capacity to produce. This finite capacity is what needs to be taken into consideration.
In more general terms, MRP ignores the operational constraints which limit how you can execute the manufacturing process. Capacity is just one subset of the constraints. There are other constraints such as sequencing relationships among operations and natural and man-made phenomenon which limit those operations. MRP provides the recipe and how much is needed, but it does not yield a plan that could be effectively executed in view of the operational constraints. The bill of materials and master schedule created by MRP cannot be followed because they ignore the operational constraints associated with executing the manufacturing process.
MRP results in an unrealistic schedule or plan. MRP does not take into consideration the limits of the dynamic process, which can become operational constraints in the process. The reality is a very dynamic process of determining what is needed, when it is needed, the operations required to assemble it, the relationship between those operations, and the things which may alter the relationships by interacting with the elements.
MRP is generally acknowledged as doing a good job of calculating, but not providing decision support, responding to changes in the environment, or providing qualitative information. MRP is a big calculator that tells one how much is needed and when it is needed, but it ignores the execution of the manufacturing process and the operational constraints thereof.
A problem with prior art is that in the past the demand on the system came from the manufacturer. The manufacturer itself decided what it wanted to make and long production runs of the same thing were favored (not many changes in the product). Due to worldwide competition in manufacturing, long production runs are less prevalent and smaller, more quickly changing runs are becoming more prevalent. Current trends in manufacturing indicate that cycle t
Crampton Myrick D.
Roadifer James L.
Smith Kevin J.
Willoughby John K.
Hogan & Hartson LLP
Manugistics Inc.
Picard Leo
Rao Sheela S.
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