An Analysis and Design of Mobile Business Intelligence System for Productivity Measurement and Evaluation in Tire Curing Production Line

AbstractBusiness intelligence (BI) system as an architecture of competencies, processes, technologies, applications and practices to support productivity measurement. It obviously needs a BI that support organization to declare any production constraints that currently or already occurred in such as tire curing industry. Overall Equipment Effectiveness (OEE) is used as a quantitative productivity measurement and become the base of company continuous improvement and evaluation. The objectives of this study are to identify critical parameters of production line in effectiveness measurement and machine utilization, analyze the requirement of information system as an Android based mobile BI System and to integrate the design into a mobile system. System requirement analyzed each interdependent measure in the real world of complexity by using BPMN 2.0. These measures are part of dashboard components in the proposed BI. The acquired data from a National forefront tire industry shows the OEE in three ratio measurement of availability, performance, and quality with 78%, 82.5% and 99.8% of scorecard respectively. In order to determine the status of production, the deployment of k-nearest neighbour (k-NN) gives 67.5% of accuracy rate. The critical parameters identification results to 8 (eight) significant constraints, which calculated using distance-based RELIEF attribute selection. Eventually this approach results big four constraints to be noted: (a) mold repair, (b) mold setting, (c) green tire shortage and (d) defect cure