Handbook of Traffic Psychology by Bryan E. Porter

Author:Bryan E. Porter
Language: eng
Format: epub
ISBN: 978-0-12-381984-0
Publisher: Elsevier Science
Published: 2011-08-14T16:00:00+00:00

2. Speed(ing) Research as a Quality Control Initiative

When building a car, auto manufacturers must address the complexities of design, planning, resources, processes, assembly, testing, delivery, sale, and customer satisfaction. The car being built can be considered a nexus because there are thousands of parts that make up many components, and these components are then assembled into a vehicle that has functionality and identity. Today, auto manufactures realize that cars of low quality are not likely to be appreciated by owners. The ability to manage multiple “assembly lines of causation” that come together to build a quality car is a daunting task. From engineers to assembly line workers, each plays a role in the building of a car, and thus each contributes to the car’s quality as revealed in some variance measure (e.g., number or rate of defects and errors). To help control variance and increase quality in the assembly of a vehicle, manufacturers turn to quality control initiatives.

One quality control practice, used by manufactures to conceptualize a complex multideterministic outcome, is the Ishikawa diagram (Mears, 1995). The Ishikawa process is a method of discovery in which subject matter experts (SMEs) across different levels and domains of product manufacturing come together to discuss, identify, and integrate the many variables influencing product outcomes. Here, the aim of the Ishikawa effort is for SMEs to assess how different variables control large and small portions of the total variance, with the goal being that as increasingly more portions of the variance come under scrutiny and manufacturing control, increasingly less overall error variance is produced. In addition, as SMEs gather to discover and conceptualize the different and varied factors influencing the quality of an outcome, SMEs begin to appreciate the big picture that reveals the interconnection between and within variables controlling outcome variance.

The Ishikawa method is scale invariant and can be applied to any system and system outcome. The Ishikawa method provides (1) an understanding of the emergent complexity from conducting a system outcome analysis (e.g., building an automobile and becoming cognizant of all of its subsystems), (2) analysis and integration of how variance is produced and how different subsystems might interact (e.g., how overall vehicle weight impacts breaking, steering, and tire performance), (3) insight into possible solutions to increase quality and control over variables producing unwanted variance, (4) a schema for mapping and visualizing the overall system of cause-and-effect chains and connections, and (5) information to manage and regulate different sources of variance (for a review of quality control tools and background, see Mears, 1995).

Figure 18.1 shows an example of an Ishikawa diagram as applied to the manufacturing of a car. This generic Ishikawa diagram is a template to foster SMEs to conceptualize and analyze obvious and non-obvious cause-and-effect relations. By bringing together different SMEs responsible for specific factors (Enarsson, 1998 and Stalhane et al., 2003), they begin to see the overall outcome (the car) as a nexus, where each SME’s work makes a contribution to the whole. The Ishikawa diagram makes visible the

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