Companies operating in the wood processing industry need to increase their productivity by implementing automation technologies in their production systems. An increasing global competition and rising raw material prizes challenge their competitiveness. Yet, too extensive automation brings risks such as a deterioration in situation awareness and operator deskilling. The concept of Levels of Automation is generally seen as means to achieve a balanced task allocation between the operators’ skills and competences and the need for automation technology relieving the humans from repetitive or hazardous work activities. The aim of this thesis was to examine to what extent existing methods for assessing Levels of Automation in production processes are applicable in the wood processing industry when focusing on an improved competitiveness of production systems. This was done by answering the following research questions (RQ): RQ1: What method is most appropriate to be applied with measuring Levels of Automation in the wood processing industry? RQ2: How can the measurement of Levels of Automation contribute to an improved competitiveness of the wood processing industry’s production processes? Literature reviews were used to identify the main characteristics of the wood processing industry affecting its automation potential and appropriate assessment methods for Levels of Automation in order to answer RQ1. When selecting the most suitable method, factors like the relevance to the target industry, application complexity or operational level the method is penetrating were important. The DYNAMO++ method, which covers both a rather quantitative technical-physical and a more qualitative social-cognitive dimension, was seen as most appropriate when taking into account these factors. To answer RQ 2, a case study was undertaken at a major Swedish manufacturer of interior wood products to point out paths how the measurement of Levels of Automation contributes to an improved competitiveness of the wood processing industry. The focus was on the task level on shop floor and concrete improvement suggestions were elaborated after applying the measurement method for Levels of Automation. Main aspects considered for generalization were enhancements regarding ergonomics in process design and cognitive support tools for shop-floor personnel through task standardization. Furthermore, difficulties regarding the automation of grading and sorting processes due to the heterogeneous material properties of wood argue for a suitable arrangement of human intervention options in terms of work task allocation.  The application of a modified version of DYNAMO++ reveals its pros and cons during a case study which covers a high operator involvement in the improvement process and the distinct predisposition of DYNAMO++ to be applied in an assembly system.

Several analytical techniques including use case diagrams, process flow diagrams (PFDs), hierarchical task analysis (HTA), failure mode and effects analysis (FMEA), systematic human error reduction and prediction approach (SHERPA), hazard analysis and critical control point (HACCP), heuristics, the Safe Living Guide and the Resident Assessment Instrument – Home Care (RAI-HC) are applied to data obtained from two pilot home visits to determine whether common failure modes, causes, effects and recommendations are yielded by the techniques. The time required to apply each analytical technique to processes uncovered from the pilot data was measured and outputs of the techniques were reviewed for commonality. Of the tools considered, SHERPA was found to return the most failure modes, effects and recommendations, while FMEA was the only human factors tool to yield causes. Additionally, FMEA and SHERPA provided a means of ranking potential failure modes based on severity and probability.

Several analytical techniques including use case diagrams, process flow diagrams (PFDs), hierarchical task analysis (HTA), failure mode and effects analysis (FMEA), systematic human error reduction and prediction approach (SHERPA), hazard analysis and critical control point (HACCP), heuristics, the Safe Living Guide and the Resident Assessment Instrument – Home Care (RAI-HC) are applied to data obtained from two pilot home visits to determine whether common failure modes, causes, effects and recommendations are yielded by the techniques. The time required to apply each analytical technique to processes uncovered from the pilot data was measured and outputs of the techniques were reviewed for commonality. Of the tools considered, SHERPA was found to return the most failure modes, effects and recommendations, while FMEA was the only human factors tool to yield causes. Additionally, FMEA and SHERPA provided a means of ranking potential failure modes based on severity and probability.

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