Advancing Architecture Options Theory: Six Industrial Case Studies

Abstract

Systems provide value through their ability to fulfill stakeholders’ needs. These needs evolve and often diverge from an original system's capabilities. Thus, a system's value to its stakeholders diminishes over time. Consequently, systems have to be periodically upgraded or replaced. Since replacement costs are often prohibitive, system adaptability is valuable. Adaptability entails the ability to modify an existing system or design of a system's architecture, such as changing, adding, removing, or replacing relevant elements as well as adjusting their reciprocal interactions. In 2008, Engel and Browning proposed a Design for Adaptability concept based on Architecture Option (AO) theory. AO fuses Financial Options and Transaction Cost theories, seeking to design systems for optimal lifetime value. They asserted that designers should balance the benefits of adaptability against its affordability. More modularity is not always better; the amount of modularity alone is an insufficient and even misleading cause of value. This follow‐up paper reports on a project, aimed at enhancing the AO theory and validating its applicability within diverse industrial environments. Through interactions with practicing system developers, the AO model was simplified and a modified Black–Scholes model was adapted into the engineering domain and successfully practiced. Six case studies were conducted within: food packaging, machine tools, automotive, aerospace, communication, and optoelectronics industries. All six industrial participants estimated, among other improvements, over 15% benefits in (1) reducing systems’ lifetime cost, (2) reducing systems’ upgrade cycle‐time, and (3) increased systems’ lifespan. These results demonstrate the industrial applicability and validity of the AO theory.

Pareto-optimization of complex system architecture for structural complexity and modularity

“…Due to such advantages, modular design strategy is widely used in engineering community to design complex system architectures using manageable and independently upgradable modules, such as fiber placement system and truck powertrain (Engel and Reich 2015). There is a whole field of research concerning modular system design and analysis methodologies.…”

“…Numerous methods to determine modularity are proposed in the literature, ranging from more engineering and functionality focused (Guo and Gershenson 2004;Martin and Ishii 2002;Mikkola and Gassmann 2003;Sosa et al 2003) to more network science centric methods (Blondel et al 2008;Newman 2010). These works are supplemented by development of other methods, such as modular function deployment (Ericsson and Erixon 1999), flexible platform development (Suh et al 2007), modular product family concept development , and modular system design based on architecture options theory (Engel and Reich 2015) to just name a few.…”

Designing Products for Adaptability: Insights from Four Industrial Cases

“…(4)Determine AAV model input parameters ( S , S′ , X , T , σ , r , I , and E ). The modeling teams used a collaborative, consensus‐building approach with a Delphi‐based (Cooke, ; Loveridge, ) technology forecasting procedure (Khadke & Gershenson, ) to estimate each input parameter (Engel & Reich, ). First, the large, periodic, research meetings provided opportunities to establish the coherent, common approach necessary to build the models.…”

“…Some models (Sharman & Yassine, 2007;Gustavsson & Axelsson, 2008) have used an options-based formulation to explore the assignment of components to modules. Engel and Browning (2008), Engel, Reich, Browning, and Schmidt (2012), and Engel and Reich (2015) developed the concept of architecture options and a quantitative model for applications within the specific domain of product architectures. However, the use of empirical data in most of this work was quite limited, and the mechanisms for trading off among alternative options remain in need of further exploration.…”

An integrated approach to product family redesign using commonality and variety metrics

“…In many cases, the bus-type modules/components are usually designed focusing on the standardization of the corresponding interfaces to be changed without affecting other components instead of reducing the number of interfaces. Engel and Reich (2015) showed that the highest degree of modularity does not always guarantee the best architecture in terms of costs; however, in order to establish a redesign strategy for components, each component's GVI value and variety needs should also be carefully considered. Although the lower housing is a bus-type component, it has the variety necessary to achieve the range of customer needs since the corresponding GVI value is in the middle range.…”