Finding the Best: Mathematical Optimization Based on Product and Process Requirements

Lüthen, Hendrik; Gramlich, Sebastian; Horn, Benjamin M.; Mattmann, Ilyas; Pfetsch, Marc E.; Roos, Michael; Ulbrich, Stefan; Wagner, Christian; Walter, A.

doi:10.1007/978-3-319-52377-4_5

Cited by 1 publication

(1 citation statement)

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“…Regardless of whether it is a radical innovation or a product improvement, PD must consider the characteristics of the market and the customers' expectations and requirements since quality aspects depend on these factors. In this sense, Lüthen et al [32] listed the quality criteria for requirements definition in PD, highlighting the need for the requirements to be understandable to all stakeholders, correctly defined to meet all expectations linked, constantly updated, feasible, measurable, and unambiguous. The authors also mentioned the need for prioritization of requirements during decisionmaking.…”

Section: A Product Development and The Requirements Involvedmentioning

confidence: 99%

Decision Method Focused on the Fuzzy Front-End Phase: A Study Applied to the Development of an Electronic Starting Block for Running Athletes

Dzulinski¹,

Braghini²,

Nascimento³

et al. 2022

International Journal on Advanced Science, Engineering and Information Technology

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In this work, we present a model to support multi-criteria decision-making in the selection of components for the initial proposals of a product or portfolio of products during the Fuzzy Front-End (FFE) phase of the Product Development Process (PD) to reduce risk and uncertainty and increase agility. The model is made of eight stages in which triangular-based fuzzy is employed to weigh customer requirements, and a direct numerical scale is used to weigh technical requirements. The main differences of this model are the identification and weighting of requirements based on different customer profiles and the identification of global customer requirements that have a direct or indirect relationship with all or most technical requirements. We applied the model in the development of an electronic starting block for running athletes with sensors that collected data to assist in training and performance improvement and were able to reduce the number of combinations of components in the FFE stage, and consequently, the development time, with the prioritization of roughly 30% of the components (10 parts of a total of 33). We highlight that there is still a need for further studies investigating the relationship of customer profiles and the impact on PDP and other ways to analyze how customer requirements impact technical requirements.

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Section: A Product Development and The Requirements Involvedmentioning

confidence: 99%