Measuring and analysing Levels of Automation in assembly systems - For future proactive systems

Production companies frequently have to meet demands and requirements, both internal and external, which trigger a plan for change in different production areas. Smaller batches and shorter time limits for set-ups between products are some of the demands on the assembly systems caused by an increasing number of product variants e.g. mass customisation. As a result, companies have to find more flexible methods for assembling their products and become more proactive in the assembly system itself. Indentifying new strategies to reduce time parameters in a system e.g. cycle-time, set-up time, throughput time etc becomes vital and can be achieved by designing the assembly system in a structured way, with the most advantageous cognitive and mechanical Level of Automation (LoA). When companies adopt automated solutions, they need to determine the correct amount of automation. There is a tendency among industry to consider automation investments as a ”black or white” decision. This may be suboptimal, as it is not always necessary to choose between humans or machines. Most manufacturing tasks usually involve a mix of manual, mechanised and computerised tasks; the companies have to consider all of these areas when automating their system. When it comes to level of automation it is a challenge to find the best solutions. It is also necessary to identify the optimal parts of the value-flow to be automated which requires a high level of knowledge about the current system. In these decisions it is essential to also consider human resources, their competence and the information flow to and from the assembly system. The aim of this thesis is to gain a deeper understanding of how companies reason when meeting their external or internal demands as well as to further develop the DYNAMO methodology with focus on the analysis steps. This is done to enable companies to design an assembly system in a structured way with the most advantageous cognitive and physical Level of Automation to cope with future changes. In order to handle these changes aimed at increasing flexibility and proactive behaviour, it is vital that companies take time parameters into account when designing assembly systems. This can be achieved by using LoA as a dynamic variable tool and the DYNAMO ++ methodology as a structured way to do it.