Productivity is an important measure of competitiveness and one important factor influencing productivity is capacity utilisation. In order to achieve high productivity, there should be no more capacity in a system than is required by the current demand rate. However, there must be sufficient capacity, otherwise lead times will increase and that may make customers choose alternative suppliers. Thus, the amount of available capacity should be balanced between the need for high productivity and short lead times. In a business environment characterised by fluctuating demand rates, a proper balance between capacity and demand rate over time requires high capacity flexibility. Capacity flexibility is the ability to rapidly adjust capacity upwards and downwards. However, before actions to increase capacity flexibility are taken, it is important that the resources paid for are properly utilised.

In the light of this, the objective of this research is to develop a support tool, aimed at capacity decisions in industry, that is based on an analysis of (i) how theoretical capacity and actual capacity are interrelated and how actual capacity can be increased, and (ii) how increased capacity flexibility can be achieved and economically justified. The application area of the research is manual make-to-order assembly systems, where many products and variants are assembled and where there are significant differences in work content between the products and variants.

The support tool aimed at in this research is expressed as a flowchart consisting of activities and decision points. Linked to the activities and decision points are formulas, rough guidelines, and decision rules. The first part of the support tool concerns the relation between the theoretical capacity (i.e. the capacity paid for) and the actual capacity (i.e. the capacity actually available). This relation is constituted by a process efficiency measure developed in this research. The measure is specifically aimed at the application area of this research. Based on this measure, rough guidelines on how to increase process efficiency in manual assembly can be derived.

When there is sufficient utilisation of the resources paid for, decisions on capacity flexibility should be focused. Given the unambiguous definition of capacity flexibility developed in this research, four factors influencing the capacity flexibility of a manual assembly system has been identified. These factors have certain attributes that can be controlled by management. Outgoing from the factors and attributes, concrete actions for increased capacity flexibility in a specific assembly system can be derived through creative thinking. Given a proposed set of concrete actions for increased capacity flexibility, the effect of the chosen actions can be predicted through discrete event simulation. Thereafter, the relative profitability of possible future capacity situations should be determined. It is proposed in this thesis that this is done in the form of an investment calculation, where the value of capacity flexibility is weighed against the cost of achieving it.