Abstract
Complexity in manufacturing systems appears under a variety of aspects, namely product, processes and operations and systems. Considering that the manufacturing environment is rapidly and constantly changing, with higher levels of customization and complexity, there is higher demand for flexibility and adaptability from companies. In this context, it seems essential to explore new approaches that can support decision-makers to take better decisions concerning the action plans that they need to launch to achieve the expected strategic and operational performance and alignment goals. Companies should become able to analyse their performance drivers, understand their meaning and the feedback loops that affect them. Therefore, decision makers can look into the future, and act even before these causes affect the transformation systems efficiency and effectiveness. This paper presents an approach oriented to multi-performance measurement in complex manufacturing environments. With this approach it is expected to overcome the gap between the operational and strategic layers of a manufacturing system, in order to reduce time when measuring performance and reacting to unexpected behaviours, as well as reduce errors when taking decisions. Moreover, it is expected to decrease the time necessary to calculate an indicator or to introduce a new one into performance management process, reducing the operational costs.
Highlights
1.1 Problem FramingDue to the increasing globalisation process and the current economic situation, the power has shifted from the producer to the costumer, forcing companies to become more aware of the market needs (Wortmann, 1997; de Ron, 1998; Chen, 2008, Hedaa, 2005; Heinonen, 2010)
In 1958 Forrester, founder of the System Dynamics approach for complex and dynamic systems, stated that management was on the verge of a major breakthrough in understanding how industrial company success depends on the interaction between the flows of information, materials, money, manpower, and capital equipment (Forrester, 1958)
Aiming to test and validate the Performance Measurement Engine (PME) developed, an industrial partner belonging to the automotive sector was selected to be used as use case
Summary
Due to the increasing globalisation process and the current economic situation, the power has shifted from the producer to the costumer, forcing companies to become more aware of the market needs (Wortmann, 1997; de Ron, 1998; Chen, 2008, Hedaa, 2005; Heinonen, 2010). The technology available may make it either too expensive or time-consuming to access the data required for effective performance measurement, and this is due to the complex and sophisticated nature of these systems This fact has led to another obstacle, which is the gap between the strategic and operational layers of an organisation. Interoperability should be seen as a key driver for an effective performance management, once it will facilitate the data flow between legacy systems and, its transformation into information This gap is a critical bottleneck for the reaction time of the company and it prevents companies from acting in a more proactive way
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