Overview of Value‐Driven Design Research: Methods, Applications, and Relevance for Conceptual Design

2019

Education Sciences

Self Cite

Students engaged in systems engineering education typically lack experience and understanding of the multidisciplinary complexity of systems engineering projects. Consequently, students struggle to understand the value, rationale, and usefulness of established systems engineering methods, often perceiving them as banal or trivial. The paper presents a learning activity based on a three-stage reverse engineering role-play developed to increase students’ awareness of the importance of correctly using systems engineering methods. The activity was developed and integrated in the Systems Engineering course given at Blekinge Institute of Technology. Its effectiveness was analyzed through semistructured self-reflection reports along with two editions of the course. The results showed the development of students’ understanding of how to use systems engineering methods. In particular, the students realized the need to deliver detailed and easy-to-read models to the decision makers. This result was in line with the achievement of some of the intended learning outcomes of the course.

Section: Introductionmentioning

confidence: 99%

A Reverse Engineering Role-Play to Teach Systems Engineering Methods

2019

Education Sciences

Self Cite

“…In Systems Engineering, new sub-systems or product components are seldom radically new designs. The necessity to comply with many requirements cascaded down from the system integrators means that design freedom is often confined to a limited set of engineering characteristics for a given product platform (Monceaux et al, 2014. Platforms play a significant role in the successful management of family products, being introduced to enable re-use of technologies, product design solutions and production system solutions.…”

Section: Supporting the Evaluation Of Platforms Variantsmentioning

confidence: 99%

“…This servitization trend can be observed in a variety of industrial sectors, from electronics to IT, from process industries to transportation and aerospace (see for instance Baines et al, 2009;Kumar and Markeset, 2011;Ahamed et al, 2013;Visintin, 2014, Wallin, 2013Wallin et al, 2015). In turn, this trend affects design and development activities: newly introduced requirements on service provision shuffle design priorities and emphasize the need for new metrics to trade-off hardware vs. service elements (Morelli, 2006;Monceaux et al, 2014). The engineering teams dealing with the development of the hardware find themselves in need to trade off 'traditional' engineering dimensions (e.g.…”

Section: Introductionmentioning

confidence: 99%

PSS cost engineering: A model-based approach for concept design

CIRP Journal of Manufacturing Science and Technology

2020

Self Cite

Manufacturing companies are increasingly moving toward delivering combinations of products and services to provide higher value to their customers. The development of such Product Service Systems (PSS) escalates in complexity when several products developed by different suppliers need to be integrated into a unique system. For first tier suppliers, it is a great challenge to model and simulate the impact of changing design variables at the micro-level on both hardware properties and governing behaviours of services over the entire lifecycle of the PSS. The paper describes a model-based approach developed to estimate the life cycle cost of a PSS hardware already at a concept design stage. The proposed approach computes the relative cost efficiency of a set of design variants using as input the data generated by the simulations run in the Computer Aided Engineering (CAE) environment. The approach allows the exploration of the design space of a PSS given by the variation of the geometry of a Computer Aided Design (CAD) model, building on the computation of customised cost modules selected by a generic list of PSS cost dimensions. For each evaluated design case, the model produces as output a unique monetary figure of the cost expected to incur by owning or using the asset throughout the lifetime. The work has been conducted in collaboration with a tier-one aerospace component manufacturer, and the application of the model is exemplified through a case study related to the development of a turbine rear structure (TRS) for commercial jet engines. The approach is most suitable for the development of complex systems in which new products and components are integrated into a shared product platform. The results are discussed in relation to the current literature on PSS cost engineering, highlighting challenges to be addressed to increase cost estimation accuracy and increase uncertainty identification and awareness.

“…Second, while it is true that monetary units are considered to be the most convenient, practical and universally understood metrics for value (Collopy 2012), it remains difficult to monetize those intangible factors that reflect the desire to obtain or retain a product or a service (Steiner & Harmon 2009;Grönroos & Voima 2013). Monceaux et al (2014) and Siyam et al (2015) claim that the SV function is too data intensive for the conceptual design phase. Even if full data would be available, value models could easily become incomprehensible to those stakeholders who do not possess specialist knowledge in the technical domain (Collopy 2012), hindering communication among the decision makers.…”

Section: Limitations Of Monetary Objective Functions For Valuementioning

confidence: 99%

Iterative value models generation in the engineering design process

2019

Des. Sci.

Self Cite

Value models are increasingly discussed today as a means to frontload conceptual design activities in engineering design, with the final goal of reducing cost and rework associated with sub-optimal decisions made from a system perspective. However, there is no shared agreement in the research community about what a value model exactly is, how many types of value models are there, their input–output relationships and their usage along the engineering design process timeline. Emerging from five case studies conducted in the aerospace and in the construction equipment industry, this paper describes how to tailor the development of value models in the engineering design process. The initial descriptive study findings are summarized in the form of seven lessons learned that shall be taken into account when designing value models for design decision support. From these lessons, the paper proposes a six-step framework that considers the need to update the nature and definition of value models as far as new information becomes available, moving from initial estimations based on expert judgment to detailed quantitative analysis.