Assembly Quality Methodology: A New Method for Evaluating Assembly Complexity in Globally Distributed Manufacturing

Abstract

As suggested by several past studies (Barkan and Hinckley, 1993; Eking, 1988; Gebala, 1992; Beiter et al., 2000; Shibata et al., 2001), complexity in the assembly process has a strong correlation with the occurrence of defects. The authors propose a new method that uses a product’s complexity to predict defect rate (Shibata et al., 2001 and 2003). This method provides metrics for assembly complexity using two engineering measures: 1) assembly time estimates and 2) ease-of-assembly ratings. Extensive field data for consumer audio equipment assembled at various manufacturing sites around the world provide the means to validate the proposed metrics. A new process-based complexity factor uses a “time standard” defined for a set of assembly tasks. Predicted defect rates, based on this process complexity, exhibit a significant correlation with actual defect data. Another factor, the design-based complexity factor, uses the “Design for Assembly” method for evaluating an assembly and allows the user to predict defect sources not captured by the process-based complexity factor. Combining these complexity factors not only improves prediction accuracy but also provides guidelines for improving the original design concept as well as each process step. The authors conclude with an example of implementing the Assembly Quality Methodology using the new complexity factors for globally distributed manufacturing.

An experimental investigation on the relationship between perceived assembly complexity and product design complexity

“…Moreover, this approach requires actual production data such as: number of defects occurred over a period of time, and does not consider assembly design complexity factor. Hence, [37] modified Hinckley's approach by combining process and design based complexity factors, where these factors are represented as a function of number of job elements in the assembly workstation, an arbitrarily selected assembly time, and completion time of individual tasks based on the method of Sony Standard Time (SST). In Shibata's method, design complexity factor is defined as the ratio between a subjectively selected calibration coefficient and ease of assembly coefficient of the corresponding workstation estimated by means of assembly/disassembly cost-effectiveness (DAC) method.…”

Considering human error in optimizing production and corrective and preventive maintenance policies for manufacturing systems

“…At the beginning of the 2000s, Shibata [41] reported that on average, 42% of the assembly defects in products such as compact disc/mini disc dual-deck players were due to human error. This work also revealed that assembly process complexity increases the human error rate and hence the occurrence of defects.…”

“…Liu et al [43] later showed the direct relationship between human error and economic loss in production and developed a loss estimation model in which the impact of human error is categorized as minor, medium, or severe. Considering 33 types of cost factor, the effect of complexity on quality in consumer audio equipment assembly has been analyzed at various sites around the world using a vast field dataset [41]. In the recent literature, researchers now recommend integrating production and human factors [44] as well as maintenance [45] and human error probability (HEP) to improve production system reliability [46].…”

Survey of recent advances on the interface between production system design and quality

“…model "think time" (when making choices), job complexity, and operator's experience. Hinckley (1993) and Shibata (2002) present models to predict defects based on the number of assembly operations in the semiconductor industry. Su et al (2010) apply a similar concept to predict defects in copier manufacturing.…”