In this article the process of rigorously setting supersystem targets in an enterprise context is explored as a model-based approach termed “analytical target setting.” Engineering design decisions have more value and lasting impact if they are made in the context of the enterprise that produces the designed product. Setting targets that the designer must meet is often done at a high level within the enterprise, however, with inadequate consideration of the engineering design embodiment and associated cost. For complex artifacts produced by compartmentalized hierarchical enterprises, the challenge of linking the target setting rationale with the product instantiation is particularly demanding. The previously developed analytical target cascading process addresses the problem of translating top level design targets into design targets for all systems in a multilevel hierarchically structured product, so that local targets are consistent with each other and top targets can be met as closely as possible. The effectiveness of linking analytical target setting and target cascading is demonstrated in a hybrid electric automotive truck vehicle example. The manufacturer introduces a new product (hybrid electric truck) in the market under uncertainty in fuel prices during the life cycle of the vehicle. The example demonstrates a clear interaction between the enterprise decision making and the engineering product development.

Engineering design decisions have more value and lasting impact if they are made in the context of the enterprise that produces the designed product. Setting targets that the designer must meet is often done at a high level within the enterprise, with inadequate consideration of the engineering design embodiment and associated cost. For complex artifacts produced by compartmentalized hierarchical enterprises, the challenge of linking the target setting rationale with the product instantiation is particularly demanding. The previously developed analytical target cascading process addresses the problem of translating supersystem design targets into design targets for all systems in a multilevel hierarchically structured product, so that local targets are consistent with each other and allow top targets to be met as closely as possible. In this article the process of rigorously setting the supersystem targets in an enterprise context is explored as a model-based approach termed “analytical target setting.” The effectiveness of linking analytical target setting and cascading is demonstrated in an automotive truck vehicle example.

Resource allocation is a core business milestone in a firm's product development process: Maximize the final value derived from allocating resources into an appropriate product mix. Optimal engineering design typically deals with determining the best product based on technological (and, occasionally, cost)

Product portfolio valuation is a core business milestone in a firm's product development process: Determine what will be the final value to the firm derived from allocating assets into an appropriate product mix. Optimal engineering design typically deals with determining the best product based on technological (and, occasionally, cost) requirements. Linking technological with business decisions allows the firm to follow a product valuation process that directly considers not only what assets to invest but also what are the appropriate physical properties of these assets. Thus, optimal designs are determined within a business context that maximizes the firm's value. The article demonstrates how this integration can be accomplished analytically using a simple example in automotive product development.

The link between manufacturing process and product performance is studied in order to construct analytical, quantifiable criteria for the introduction of new engine technologies and processes. Cost associated with a new process must be balanced against increases in engine performance and thus demand for the particular vehicle. In this work, the effect of the Abrasive Flow Machining (AFM) technique on surface roughness is characterized through measurements of specimens, and a predictive engine simulation is used to quantify performance gains due to the new surface finish. Subsequently, economic cost-benefit analysis is used to evaluate manufacturing decisions based on their impact on firm's profitability. A demonstration study examines the use of AFM for finishing the inner surfaces of intake manifolds for two engines, one installed in a compact car and the other in an SUV.