Barriers to accomplishing effective Design Reviews include the following: — The DR team consists of people who are unevenly matched in skills and knowledge. — Product developers tend to press on with little communication among related departments. — The product development schedule is often cramped and allows for little time and flexibility for changes in response to DR. — The DR team may lack the expertise, resources or authority to to make the process effective. — During the concept phase of the design process, the DR team has little basis on which to provide feedback. — Product Design managers view DR to be separate from design, thereby leaving little scope for conducting DR of drawings, specifications etc. — DR is an additional demand on both the design and engineering teams, both of which are under constraints.
Authors experience in industrial engineering, physical medicine and rehabilitation, and as Editor-in-Chief of the International Journal of Industrial Engineering.
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NPD process needs more examination of Product Characteristics, Marketplace Characteristics, Strategy Synergy, and Product Quality as predictors of new product performance.
Literature review of 815 NPD articles published in the 10 leading marketing, management, NPD and R&D journals from 1989 to 2004.
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Modular product architecture is a product generation strategy where one subsystem is created, and then efficiently expanded upon and split into many varietal products.
Case study analysis
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Create and maintain high levels of integration between Marketing and Research & Development functions and product prototype development, product launch and cycle times will all have increased proficiency. Market forecast accuracy and technological core competency fit will also be improved with function integration. Be sure to implement integration at step 4.1.
Survey. A multiple regression analysis revealed significance between integration and: product prototype development proficiency (F=70.80); product launch proficiency (F=122.74); product development cycle time (F=13.84), market forecast accuracy (F=75.65); and technological core competency fit (F=39.64), all interactions significant at the p<.001 level.
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Design Review does not create good ideas, but instead ensures that good ideas work as well as possible. Design Review involves six actions: 1) Collect and compile information; 2) Define quality targets; 3) Evaluate product and process designs and supporting operations; 4) Proposition of improvements; 5) Definition of subsequent actions; 6) Confirmation of readiness to move to next stage.
Authors experience in industrial engineering, physical medicine and rehabilitation, and as Editor-in-Chief of the International Journal of Industrial Engineering.
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Design for Quality/Design Review — the systematic process of bringing complex products to the market quickly, while ensuring product design quality meets customer requirements, within cost and time constraints. Design Review is is generally applied at the general design stage, and to a lesser degree, at the detailed design and pilot building stages. Design Review is based on two premises: 1) Make the best of available knowledge and technology from both in-house and outside resources; 2) Do everything to resolve problems as they arise. Avoid passing them downstream.
Authors experience in industrial engineering, physical medicine and rehabilitation, and as Editor-in-Chief of the International Journal of Industrial Engineering.
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Failure Knowledge Network (FKN) — captures and inter-relates mechanical product quality knowledge from five areas: (i) the connection between failures and product functions, (ii) the relationship between failures and product components, (iii) the correlation between failures and organizations, (iv) the association between failures and product processes, and (v) the conjunction among different failures. FKN information is represented in a four-dimensional matrix that includes components, functions, processes and organization. Each element in the matrix is a failure scenario and represents the related failures within the corresponding dimensions. Conventional factors of failures are embodied in the FKN representation. They include event, detection, effect, severity, solution weight, cause, monitor, reappearance, operation, efficiency and precaution. The indexes of each factor are provided by subject matter experts and are set in accordance with the correlation between corresponding characteristics and failures
Failure knowledge based decision-making in product quality.
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The cost of reworking a design is based on three factors: 1) As more is time spent on an activity using outdated information, the amount of cumulative work that must be modified will be larger. Hence, rework time is an increasing function of the time between two successive incorporations of new information; 2) Rework time is dependent on how much the information and the activity are related. In general, a change in major input needs longer rework time than a change in minor inputs; 3) The degree of sensitivity which implies the robustness of the activity to changes. A larger degree of sensitivity indicates a longer rework time frame.
Mathematical model creation and analysis.
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Be flexible with managing resources to have higher levels of success with product development execution.
Survey of 120 development projects from 57 firms. Hierarchical regression was significant, beta = .179 at p<=.1
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If your company's strategy is that of an analyzer, one which makes new concepts or innovations more efficient, consider using design tools such as CAD/CAM (computer aided design/manufacturing) to improve your new product development performance.
Survey. Analyzers were found to significantly make more use of CAD/CAM tools than defenders.
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Technical Resources, Skills & Activity: A company's technical resources (including production resources, skills of engineering staff, experience in R&D) are important factors in successful products.
Source: In: Calantone, R.J., diBenedetto, C.A. (1988)

Use computer based tools to help shorten design time, reduce costs and improve quality.
Source: Karagozoglu and Brown (1993). In: Koufteros, X. & Marcoulides, G. A. (2006)