Cognitive Automation in Mixed-Model Assembly Systems
Customization and personalization of products and services has become the new standard of doing business. In order to provide highly customized products at a reasonable price flexible processes are needed. One example of how a company may supply its customers with variation is VOLVO where the C30 model can be configured to as many as 56 million unique variants. Increased variants puts great strain on the production and assembly system. The product variation creates a vast need for information to support the assembly operators working in the final assembly. As an increased number of choices are required, support by cognitive automation for assembly operators working in a mixed-model assembly environment is needed. In production, especially in an assembly context, cognitive automation aims to support decision making in order to ensure production of error-free products. Increased cognitive automation could improve the operators’ work situations and decrease their workload while retaining the same physical automation. However, cognitive automation tends to be less developed than physical automation.
The objective of this Licentiate thesis is to examine how cognitive automation can best be used to support operators in mass customized assembly. Three case studies were carried out at two companies, aimed at identifying their needs concerning cognitive automation. Results of these studies showed that increased product variance caused by mass customization creates a complexity, which may impact the number of assembly errors. One cases study aimed to develop a mobile ICT tool based on a smartphone application and test its possible implementation and benefits. The use of cognitive automation such as a mobile ICT tool can reduce the error rates in complex assembly environments. Although high levels of cognitive automation exists, the actual use of such support can be low, which might be a result of support not designed for the end user. Therefore an increased level of automation does not always provide more support. By altering the carrier and content, the cognitive support can be enhanced to fit the context e.g. mobile information carriers in large assembly stations. Providing more precise cognitive automation can thus target the challenges of more parts and procedures associated with mass customization.
Keywords: Cognitive Automation, Information, Assembly Systems