Manufacturers are under more competitive pressure than ever before to adopt robust design-stage cost management practices like Design-to-Cost. Traditionally, engineers have been asked to deliver designs that met a cost target but were not given a tool that could help them dynamically determine the cost of their designs. Fortunately, such tools are now available.
Systematically analyzing key cost drivers for a manufactured product, however, is more than a matter of running a few calculations. Truly integrating cost-optimization at the design stage is, in fact, a complex business problem.
This complexity stems from the dynamic interaction of design choices with the full breadth of a product’s cost structure. These interactions range from the straightforward (more material drives more cost) to the less obvious (adding or even modifying a simple feature, like shrinking a casting hole, can shift the manufacturing process and change costs).
In this article, we examine some prototypical cost management issues and look at how managing these cost drivers requires developing a more systematic approach for considering alternatives at the design stage—a need that requires the right tools.
Complex Cost-Drivers in Operational Context
The nature of product design means that virtually every cost driver is densely interwoven with broader design concerns, from form, to functionality, to manufacturability. Even a seemingly simple change can create a cascade of secondary cost-fluctuations throughout the design. And these cost changes are not necessarily intuitive.
Even choices constrained to a single manufacturing floor can introduce myriad alternatives. When the scope of decision-making extends to an international supply chain, quantifying alternatives effectively becomes impossible without specialized technology tools (more on that below).
A few example scenarios of complex cost-interactions help illustrate why. While the relevance of specific cost drivers varies substantially from industry to industry, these examples are representative of the complexity, interactivity, and non-linear cost implications of design choices for manufacturers dealing with a broad range of commodities and production processes.
- Unanticipated Secondary
Manufacturing Processes and Cost: Design
choices determine how a product can be produced. A secondary machining
requirement necessitating an additional machine set-up and associated cycle
time can potentially add significant cost.
However, if the machining process is already utilized to make another feature in the part, then the additional cost of adding a machining requirement may be small.
Take the example of a casting with a small hole that needed to be machined because the casting process was not suitable. Adding an additional machined hole to this design would add far less marginal cost than the first.
- Volume-Driven Effects: the effective impact of a design choice can vary widely depending on expected production volume. This fact can make design choices difficult to evaluate at face value.
For instance, an engineer may notice that employing a feature, such a series of holes laying close to a bend, adds a minimal amount of cost for a high volume part that is made via a stamping process, but, it may add more quality risk and cost to a low volume part that is made via a laser/bend process.
- Tolerance Selection Driving Unnecessary Costs: product design often involves a degree of arbitrary conservatism in tolerance selection—when in doubt, specifying a tighter tolerance may offer better reliability.
This practice risks a design where unnecessary tolerance margins drive cost-increases, at times even forcing the move to a different production process. Visibility of tolerance specifications’ cost implications is needed to encourage designers to more carefully consider the true tolerance requirements.
A Product Cost Estimation Toolkit that Reflects the Cost of Design Choices
The technological and economic complexity driving the final cost of manufactured products is not new, of course. But the presence of viable solutions for cutting through this complexity with design-level analytics represents a novel opportunity.
In the past, the complexity of cost estimation resulted in simplified, less-accurate approaches—comparing a product to past projects, tallying input commodities, and using back-of-the-envelope calculations. While sometimes capable of capturing a handful of fundamental design choices, these methods can ultimately only provide rough order of magnitude estimates. However practical, these abstractions can’t begin to provide a truly systematic account of the huge array of factors that drive manufacturing cost—much less provide data-driven comparisons of strategic alternatives.
The right manufacturing cost estimation software should do something else entirely—provide comprehensive analysis that reflects the full breadth and interactivity of manufacturing and design choices and their cost implications.
To do so, this software needs mechanisms for analyzing everything from specific manufacturing process feasibility, to material consumption calculations, to labor and raw material costs, modeling complex interactivity to generate actionable insights in real time.
aPriori, for example, works directly with 3D CAD files to automatically analyze a design—and every potential manufacturing routing’s true impact on final cost. Rules-based analysis covering dozens of specific manufacturing processes to make this level of detail possible.
By providing a variety of cost breakdown views, design-to-cost feedback, and comparisons of alternative manufacturing processes across different production facilities, aPriori makes it possible to “see the forest for the trees” in cost management. You can see a live demonstration of aPriori being utilized in support of a design-to-cost effort here.
Or, for a deeper dive on this topic, you download our whitepaper on product cost management here.