Design and Implementation of Downtime Management System for Assembly Production : Software specification and practical challenges

Abstract: The usage of information technology (IT) systems has become an integral part of assembly manufacturing. Supervisory control and data acquisition (SCADA) systems are widely used in order to control production cycles and monitor equipment such as conveyor belts. Other common IT systems are related to logistics, data analysis, or organizing of incoming and outgoing orders. In this thesis we create a model for the IT systems at the fuel pump and fuel injector manufacturer Scania XPI. One model is developed for the current state of the IT systems at Scania XPI, and one model is developed detailing the future state. The current state model consists of charts showing where in the production process that data is transmitted between which IT systems. This thesis utilizes the current state model in order to suggest improvements to the IT systems. These improvements are detailed in the model for the future state of IT systems at Scania XPI. Overall equipment efficiency (OEE) is a measurement of the performance of an industrial operation based on the percentage of up time running at full capacity compared to the available run time. Measurement of OEE requires that only downtimeduetointernal circumstances within the operation is taken into account, and that any potential quality deviations due to the operation are accounted for. Taking into account the variability of manufacturing processes, this thesis proposes solutions to issues in data processing required to measure the efficiency of operations in assembly manufacturing, such as identifying if process breakdowns are caused by external factors. The proposed solution is a system called "Process data analysis system" (PDAS), which uses the recorded machine statuses throughout operation in order to calculate process downtime and OEE. PDAS was implemented using the incremental waterfall model as a software development methodology. PDAS was evaluated by conducting four groups of experiments and a comparison to the PUS (processuppföljnings system) at Scania XPI. Automatically classifying downtime events as planned or unplanned allows PDAS to give an accurate view on the efficiency of the assembly production. The software can be used at Scania XPI and it’s functionality has been verified on assembly production running in ordinary conditions. We show that software can be developed to process industrial data in order to measure assembly line efficiency. Eventually, design and implementation of a downtime management system for assembly production is achieved as a final product of this thesis.