Improving Profits with Materials Optimization in Manufacturing For a Major Aerospace Company
Chris E. Nunezk -- Centor Software CorporationIntroduction:
Every large manufacturing organization that designs and produces a complex product like an electronic switch, an aircraft engine or an automobile must decide what type of material should be used for each and every part that goes into their products. Sometimes the material selection decision is left up to the suppliers and in other cases the suppliers must meet the material specifications of the manufacturer. Typical raw materials range from steel, plastic, composites, glass or rubber.
The material selection decision plays a vital role in determining downstream costs related to producing the end product.
According to AMR Research, in many industries more than 60% of overall procurement costs are spent on direct materials. This includes the cost to buy and process the raw materials that make up each part of the product. According to testimony made in 1999 by Daniel T. Griswold, of the House Committee on Ways and Means, the average five-passenger sedan has $700 worth of steel in it. These figures do not include any of the costs to "fabricate" the steel into the desired shape.
There are hundreds of thousands of raw material choices-from unique grades of steel, aluminum and titanium to various formulas of plastics made available from hundreds of suppliers.
Each material type, class and grade has a unique set of properties. These properties enable the parts to be lighter, stronger, withstand higher temperatures, or improve mean time between failures. Certain materials are better suited for human contact, while others cost less to process into the desired shape. Herein lies the challenge and the opportunity.
Material Properties
Design engineers make their material selection decision based on cost, physical, chemical or mechanical properties. Each unique type of material can have many interactive properties like: shear strength, friction coefficient or tensile strength. The data is typically generated from a material test lab either by the manufacturer or by the supplier of the raw material.
Today's design engineers use simulation software to predict the performance of individual parts. They use this software to answer design questions. For example, how will the part break or bend under certain load conditions? How will the part expand or contract and will it cause problems in the field? Can the part be cast or molded efficiently and affordably? All of these types of questions can be predicted using simulation software, but they require material properties as input to the software's advanced mathematical formulas and equations.
Materials Optimization:
Without a single source for material properties information, most engineers find the data from textbooks, handbooks, suppliers or previous experience. Given this lack of consistency, the tendency of engineering functions is to be conservative when utilizing this data. As a result, engineers will apply a large safety margin in their analysis to reduce the risk of failure, and therefore avoid the severe economic impact that comes with flawed designs. Unfortunately, this "safety margin" can cause a part to be over designed, perhaps heavier than actually required for example, and can significantly increase the overall cost to produce the part.
One way a Materials Selection Optimization System can be leveraged is to allow engineers to be more confident and use a lower "safety margin." This is accomplished by having shared access to a more complete body of knowledge on material properties. Having a central repository of material property information effectively allows experienced engineers to share their expert knowledge with a less experienced designer.
This sharing of knowledge can translate into significant cost savings in raw material and processing costs for the manufacturer as "over-engineering" is reduced, thereby reducing overall part characteristics such as thickness and weight.
ROI Calculator Methodology:
In order to estimate the cost savings and ROI benefits the following ROI calculator was developed. It focuses on three key areas:
SECTION 1: Tangible Benefits:
Tangible benefits relate directly to annual cost savings of deploying a Materials Optimization System and can be calculated based on knowing a number of inputs. These inputs will vary based on each manufacturing organization.
Products Shipped Per Year
Cost of Raw Material
Total Weight Per Product (lbs)
Price Per Product ($)
Number of Material Data Sources
Weight Reduction Factor
Data Management Savings
Reduction in Materials Testing
Reduction in Raw Material Costs
Annual Cost Savings
SECTION 2: Non-Tangible Benefits
Non-Tangible Benefits will relate directly to possible increased sales and reduced expenses due to the productivity enhancements that a Global Material Optimization System will bring to the organization.
Higher Product Quality
Faster Time-to-Market
Number of Lookups (engineers to material properties)
Engineering Time Savings
Reduced Warranty Costs
SECTION 3: Costs to Deploy
Hardware Costs
Software Costs
Data Conversion and Training Costs
Conclusion
While any large information system project is an expensive and complicated endeavor, making an investment to share mission-critical information and put in place a "best practice" process can have a dramatic impact on product quality and profits.
A more complete version of Dr. Nunezk's talk (as of October 16, 2000) is available on-line at the following URL: http://www.iss.org/magazine/WebOnlyArticles/Nunez/Nunez-0108.htm. This may become a "dead link" at any time.