Simulation's New Old Frontier6 Jun, 2006 By: Jeffrey Rowe
Digital analysis of the manufacturing process isn't simple, but it offers big dividends
One of the most significant trends in mechanical CAD over the past few years has been the increasing presence and acceptance of digital simulation and analysis. Once relegated to the later stages of design, simulation and analysis now are often employed relatively early in the in the product development cycle -- and that's a good thing. Also, simulation and analysis products are now usable by a great many designers, not just those who have advanced math degrees. So, simulation and analysis are becoming ingrained in product development, but what about their use in the manufacturing process?
In the manufacturing context, simulation and analysis are used to digitally define and test production processes. The main purpose of manufacturing simulation is to increase productivity by determining throughputs, minimizing process and material bottlenecks and making better use of plant and personnel resources -- in other words, workflow optimization. Simulation and analysis for manufacturing have been available for a while but have not gained nearly the popularity of their counterparts in design. As a matter of fact, manufacturing simulation is hardly new; it's been around nearly as long as mechanical CAD.
Today, manufacturing simulation is well integrated and works in tandem with models created with CAD software, in which both product and process get equal consideration, at least in theory. An important part of the merging of product and process simulation was the advent of PDM (product data management). PDM is important because it provides and promotes data reuse of existing designs; better-organized and more searchable data; and collaboration and use of the data by a much larger group than previously possible. Many of the same benefits that product design automation enjoyed with PDM are now being realized in manufacturing.
Although it has advanced significantly, manufacturing simulation still lacks some of the capabilities and benefits offered by product simulation systems. Why? A couple of reasons account for the disparity. First, there's an issue related to timing when a simulation should be performed for evaluating and validating the sequences of different manufacturing processes. Like any component of the product lifecycle, manufacturing is but a fraction of the overall picture. Great care must be taken and valuable time must be spent in evaluating manufacturing operations that might ultimately change because of product requirements or constraints. This limitation is something that will probably never be completely solved, but with experience, manufacturing simulation can definitely streamline and optimize manufacturing operations.
The second major limitation is that although manufacturing is indeed integrated into the product development cycle, manufacturing activities and software applications (including simulation) are often still regarded as isolated from the rest of the process. If the design phase is sometimes reduced to throwing projects over the transom between the design and engineering departments, it's often worse between engineering and manufacturing.
A significant problem in properly implementing manufacturing simulation is data acquisition and the complexities that arise in trying to make sense of it all. Dealing with 3D product CAD data is one thing, but other types of data are essential, including information about the manufacturing environment itself, such as statistical data on machine throughput rates, models of production machines, material handling equipment, robots and so forth. Also required is data on the physical nature of the manufacturing floor, such as distance between work cells and how parts and assemblies in process are moved through the factory. Then there is the human element, and simulating this can be quite an undertaking as attempts are made to increase and optimize productivity while ensuring worker safety.
Big Challenges -- and Payoffs
As you can see, piles of data can become mountains in fairly short order. In addition, acquiring all this data is a time- and labor-intensive process, and is probably the main reason that more manufacturing simulations are not performed and why it so difficult to ultimately optimize manufacturing operations. However, experience in data acquisition and use for manufacturing simulation can provide big dividends.
Manufacturing simulation can be viewed in much the same way as product simulation, except that a virtual manufacturing process, rather than a physical object, is being digitally prototyped. As with product simulation, the goal of manufacturing simulation is to catch and correct errors early in the game, before generating formal production process plans. Ideally, the simulation provides a greater understanding of the many steps involved in the manufacturing process, which would have been difficult or impossible before the advent of digital simulation techniques.
Although they are similar in some ways, manufacturing simulation and manufacturing visualization are two different animals with different requirements and benefits. In the next edition of MCAD Tech News, I'll discuss the similarities and differences of the two, and how they are being used.
About the Author: Jeffrey Rowe
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