The Best Nesting is Optimation as Profiled in AutomationMedia

The Best Nesting is Optimation as Profiled in AutomationMedia.com

For thirty years Optimation® (www.optimation.com) has been the world leader in Part Nesting for Optimized Material and Labor utilization. Consistently providing product advancement leadership to industry, the company’s new Nesting Technology, AxiomVE make previous nesting methods obsolete. The new technology, Vision Emulation™, allows the system to “see” the shape of parts, just as human eyes would view them. When a person looks at a part, they see the whole shape and any special features on the part. This information is then used to determine if the part will fit in an area of the nest. Vision Emulation eliminates excessive trial and error as well as excessive rotation. In the current issue of AutomationMedia.com, manufacturing journalist Thomas R. Cutler profiles Optimation and the need for benchmarking the best nesting solutions. The article, titled “The Test: Benchmarking the Best Nest” can be read in entirety at http://automationmedia.com/TRCutler.asp?ID=%2056. Benchmarking against a current method of producing parts using real world requirements is the only efficacious way to determine if new methods, such as Vision Emulation and Multi-Dimensional-Combinatorial-Nesting technology, are indeed improvements. Always having the highest level of automated productivity and cost cutting technology is quantifiable. Quantify a specific number of parts that are actually used in production; only then can optimized manufacturing metrics be compared and the best nest discovered. Past methods of nesting have followed rules that reduce the very large number of combinations to a manageable few. The purpose of a heuristic rule set is to eliminate most of the calculations required to obtain a solution. Most nesting heuristics use some variation of the “First Fit” heuristic. The “First Fit” heuristic uses the following general steps: 1. Order the parts from largest to smallest. 2. Place the largest part on the raw material. 3. Rotate the part to the orientation that brings it closest to the nesting corner. 4. Place the next largest part on the raw material. 5. Rotate the part to the orientation that brings it closest to the nesting corner. 6. Repeat steps 4 and 5 until all parts are nested or until no more parts will fit. This method is modified by adding fewer or more rotations, placing some parts in holes of other parts, reordering the list by other attributes such as longest or greatest perimeter. According to Michael D Lundy P.E. and President of Blue Springs, Missouri-based, Optimation, “In all cases heuristics are blind. In order to prevent the heuristic from selecting a nest that is infeasible, constraints are applied to the list. A filter is applied to prevent parts that are due in the future from being considered. Another filter will limit the list of parts to insure that too many tools are not required by the set of parts in the list. These filters limit many of the possibilities that are feasible. The result is a sub-optimal nest that is feasible but wastes material and productivity.” Lundy’s company approached this problem with a dynamic method of evaluating optimal results. Multi-Dimensional-Combinatorial-Nesting technology (MDCN™) is a new technology which transcends previous nesting methods. Unlike heuristics, the combinatorial nesting approach uses fathoming to eliminate infeasible solutions and sub-optimal solutions. When Vision Emulation is applied with MDCN, the part selection process is greatly enhanced and brings a powerful toolset for finding and placing the right parts in combination with other parts to achieve the optimal nest. Optimation offers benchmarking against any other method of part nesting; recent benchmarks have show improvements up to 15% in material efficiency alone. Optimation www.optimation.com Michael D Lundy P.E. Opti1@optinest.com 877-827-2100