A measure of Overall Worker Efficiency applied at Volvo Cars
Conference contribution, 2017
The are many indicators used in industry to measure the performance of the work force. However, there is a lack of theoretical foundation and detailed descriptions of what measures to include and how to measure. Overall Worker Efficiency (OWE) is suggested in this article as a standard indicator to be applicable in all sorts of industries and levels of automation. The name OWE indicates its similarities to OEE (Overall Equipment Effectiveness). The theoretical design is similar, it is the ratio of “value adding” time to the total planned working time. However, there are many difficulties to define what value adding time is and what to include in the planned working time. Several variants of OWE are presented in this article. The selection of variant to be applied for a company should be based on the purpose for the measure. OWE can be used to follow up losses on station or line level, it can be used during a ramp-up phase to follow the number of extra personnel needed, or it can for example be used to monitor the need for support staff such as maintenance or material handling personnel.
The OWE measure has been applied and tested at Volvo Cars engine plant in Skövde. That is a suitable test case since the company has a good control of their time bases. OWE requires that the intended cycle time or ideal working time is known and set by an objective method such as a pre-determined time system. In Volvo’s case MTM-SAM (Method Time Measurement – Sequenced-based Analysis Method). Data from the final assembly line was used for the test purpose and a practical work procedure was developed for Volvo.
The OWE measure has the potential to be applied in all kinds of manual or semi-automatic production. The precondition is that the available time data has a good quality. The OWE measure can be used together with OEE in semi-automatic work and there will be a trade-off between them in practice where the decision of which one to maximize will depend on the bottle-necks and whether for example total cost or minimum lead-time is most important.