SBCE Background

According to Clark and Fujimoto (1991), the earliest decisions in product development have the largest impact on the overall quality of the product (effectiveness) and the overall cost of the project (efficiency). Many approaches to engineering design are focussed on reducing cycle time following the famous motto “do it right the first time”. In terms of design strategy, this has often been translated into a need to propose the right solution as fast as possible. As observed by Sobek and Ward (1996), when dealing with the development of complex products, many US companies force the engineering teams to propose a feasible concept quickly so that it can then be optimized through numerous iteration loops. This pattern is understood as point-based because it focuses on one solution at a time and progressively refines it until all stakeholders are satisfied with the outcomes. Figure 2.5 illustrates this view.

Figure 2.5: Point-based approach to the design of a complex product. Adapted from (Ward et al., 1995)

Another design strategy, the set-based approach, has been the subject of a number of publications over the past 20 years. It is one of the pillars of lean thinking applied to product

development, again, observed particularly in the automotive industry through companies such as Toyota, Honda, or Denso. Here, engineers may reason and communicate about acceptable range of parameter’s values instead of single best value at a time. Set-based design allows windows of possibilities to align gradually and therefore the best of all worlds to be projected. It is rather a convergence process than an evolution (Sobek & Ward, 1996). Participants bring sets of possibilities to the table and juxtapose them to find intersection of feasibility rather than successively criticizing and modifying a single option (Liker, Sobek II, Ward, & Cristiano, 1996). Figure 2.6 illustrates the approach.

Figure 2.6: Set-based approach to the design of a complex product. Adapted from (Bernstein, 1998)

Set-based approach to problem solving has already proven to be efficient in some simple problems like selecting a group meeting time. Participants may submit their preferences and then the meeting organiser finds the most convenient time in the intersection of all, i.e. set-based solving. In contrast, point-based solving may involve either: participants compromising a meeting time one after the other until a satisfactory time emerges, or participants having a meeting to decide the meeting time, or finally, some powerful members forcing everyone to comply with a selected time. Sobek, Ward and Liker (1999) described the three principles of SBCE which, according to Ghosh and Seering (2014), have remained the same used for SBCE discussions and implementations across the research literature and industrial applications.

1. Map the design space:

 Define feasible regions;

 Explore trade-offs by designing multiple alternatives;

 Communicate sets of possibilities;

2. Integrate by intersection:

 Look for intersections of feasible sets;

 Impose minimum constraint;

 Seek conceptual robustness;

3. Establish feasibility before commitment:

 Narrow sets gradually while increasing detail;

 Stay within sets once committed;

 Control by managing uncertainty at process gates.

Several methods like the morphological chart (Cross, 1989), the method of controlled convergence (Pugh, 1991), the Design-Build-Test cycle (Wheelwright & Clark, 1992), the fuzzy inference based concept convergence process (Augustine, Yadav, Jain, & Rathore, 2010) and the Configurable Component based platform i.e. product platform strategy (Wahl & Johannesson, 2010) share strong similarities with SBCE (design strategy) in the sense that they all use the

exploration of multiple alternatives to converge within the design space or the design bandwidth². The main specificity of SBCE is twofold: (1) In SBCE, speciality groups can independently analyse their design options (sets of design alternatives) then intersect at integration events which then eliminates the iterative path that is problematic in point-based approach (Bernstein, 1998;

Sobek & Ward, 1996); (2) SBCE delays decision to learn by experimentation (extensive prototyping) and additionally front-load the design/development (reuse/recycling of existing knowledge) before narrowing the design space by elimination of unfeasible designs (Morgan &

Liker, 2006; Ward & Sobek, 2014). Prototyping, learning and the reuse of existing well-structured information and knowledge are therefore important aspects of SBCE. To elaborate, Ghosh and Seering (2014) extracted seven characteristics of set-based product development after thoroughly analysing the literature on set-based thinking in the engineering community and beyond: (1) Emphasis on frequent, lo-fidelity prototyping; (2) Tolerance for under defined system specifications; (3) More efficient communication among subsystems; (4) Emphasis on documenting lessons learned and new knowledge; (5) Support for decentralized leadership structure and distributed, non-collocated teams; (6) Supplier/subsystem exploration of optimality and; (7) Support for flow-up knowledge creation. The seven characteristics are used to form a framework for analysing the research works that exhibit set-based practice. As a result of the review, Ghosh and Seering (2014) acknowledge the fact that set-based design is not formally defined and they point out the tendency of the majority of authors to mainly study the set-based process as perceived and inspired from Toyota’s practice and philosophy. The observations are then refined to distill two fundamental overarching principles that govern Set-Based Design (SBD) i.e. (A) Considering sets of distinct alternatives concurrently and, (B) delaying convergent decision-making. It is argued that the principles are fundamental in the sense that they can manifest themselves in all phases of the design process, not limited to the conceptual phase or the interface with detailed design phases (Ghosh & Seering, 2014). These authors note that it is not possible to guarantee that the two principles are the only ones governing SBD, but they are sufficient to contrast SBD and traditional Point-Based Design (PBD) by defining one as the negation of the other. As such, propositional logic is used to express SBD ≡ A ˄ B, then, by

2 The concept of the design bandwidth in product platform design is described in (Berglund & Claesson, 2005).

considering PBD is simply “not SBD”, PBD is formed as the negation of the conjunction. This, by De Morgan’s law, is the disjunction of the negations: PBD ≡ ¬SBD = ¬(A ˄ B) = ¬A ˅ ¬B, which means that the lack of either principle A or principle B will rule out a design/development process as set-based. Both principles have to be followed to make a design/development process set-based. Ghosh and Seering (2014) conclude their study by listing a number of research areas requiring exploration. In details, it is said that it will be constructive to determine what factors and situations are more suitable for the application of SBD vs. PBD, understanding the related cost, performance and trade-off. In addition, it is noted that research need to better identify works that are not explicitly associated with set-based but which disclose characteristics of SBD and can actually improve its understanding and implementation. To continue on Ghosh and Seering’ path, the remaining part of this chapter concentrates on a systematic literature review of SBCE using a new SBCE analysis framework.