EVOKE: A Value-Driven Concept Selection Method for Early System Design

Abstract

The development of new technologically advanced products requires the contribution from a range of skills and disciplines, which are often difficult to find within a single company or organization.Requirements establishment practices in Systems Engineering (SE), while ensuring coordination of activities and tasks across the supply network, fall short when it comes to facilitate knowledge sharing and negotiation during early system design. Empirical observations show that when system-level requirements are not available or not mature enough, engineers dealing with the development of long lead-time sub-systems tend to target local optima, rather than opening up the design space. This phenomenon causes design teams to generate solutions that do not embody the best possible configuration for the overall system. The aim of this paper is to show how methodologies for valuedriven design may address this issue, facilitating early stage design iterations and the resolution of early stage design trade-offs. The paper describes how such methodologies may help gathering and dispatching relevant knowledge about the 'design intent' of a system to the cross-functional engineering teams, so to facilitate a more concurrent process for requirement elicitation in SE. The paper also describes EVOKE (Early Value Oriented design exploration with KnowledgE maturity), a concept selection method that allows benchmarking design options at sub-system level on the base of valuerelated information communicated by the system integrators. The use of EVOKE is exemplified in an industrial case study related to the design of an aero-engine component. EVOKE's ability to raise awareness on the value contribution of early stage design concepts in the SE process has been further verified with industrial practitioners in ad-hoc design episodes.

Value chain and stakeholder‐driven product platform design

“…Isaksson et al introduced a value‐driven design methodology based on an information‐driven approach and demonstrated the methodology using an industrial aircraft development case study. Bertoni et al suggested an approach for implementing a value‐driven design to product service systems, and later proposed a value‐driven concept selection method known as early value oriented design exploration with knowledge maturity (EVOKE) . Topcu and Mesmer developed an end‐user value‐based demand model to be used in value‐driven design to maximize value of the system designed.…”

Supporting Early Stage Set-Based Concurrent Engineering with Value Driven Design

“…The last step of the process focuses on running the trade-off analysis on a number of design variations of the concepts identified with TOPSIS. This step is based on the application of an extended version of the EVOKE (Early Value Oriented Design Exploration with Knowledge Maturity) approach (Bertoni et al, 2018). EVOKE initially cascades down VCS information into a list of rank-weighted value drivers that is relevant for the specific technology development project at hand.…”

“…It encompasses both the screening of possible technologies and the assessment of different design concepts in the feasible design space from a value perspective. The approach is based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) (Kim et al, 1997), a multi-criteria decision analysis method for technology screening, and it further adopts an extended version of the EVOKE approach (Bertoni et al, 2018) to enable the automatic calculations of the design merit of multiple design variations in the feasible design space. The approach is described in the paper through its application to the case study of the development of a new generation turbine rear structure (TRS) for a commercial aircraft engine.…”

Modeling resale value of road compaction equipment: a data mining approach

“…The 'Receiver State Parameters' approach proposed by Kimita et al (2009) (Figure 5), for instance, is based on the use of an exponential function, similar to the one proposed by Xing et al (2013) to measure the functional fitness of a PSS hardware in a time perspective. The CODA model (Eres et al 2014) and the EVOKE model (Bertoni et al 2018) are two QFD extensions use non-linear merit functions in PSS design to map the engineering characteristics of a product to its expected value contribution. The main challenge when working with these more sophisticated mappings is that the nature and type of value functions is difficult to determine with precisions.…”