Toshiba's predictive maintenance system also helped to optimize equipment performance and extend its lifespan. By analyzing this data in real-time, Toshiba was able to proactively schedule maintenance before a failure occurs, minimizing downtime and reduce maintenance costs. By using machine-learning algorithms and statistical analysis, Toshiba could identify patterns and anomalies in the data that could indicate potential equipment failures. Toshiba collected data from various sensors and sources to predict when maintenance was required for its equipment. By identifying issues before they become major problems, predictive maintenance can help to prevent unplanned downtime and reduce costs. Predictive maintenance involves collecting and analyzing data from sensors and other sources to identify patterns and anomalies that can indicate when equipment is likely to fail or require maintenance. Considering downtime costs the average manufacturing plant more than US$172mn per annum, all reductions can be considered valuable. In one example, the Toshiba Corporation used data analytics to enable predictive maintenance, which is a Lean principle that aims to minimize downtime and reduce costs by identifying potential equipment failures before they occur. By analyzing data, manufacturers can identify and eliminate waste, reduce defects and improve overall quality, which are all key objectives of both Lean and Six Sigma methodologies. Toshiba: The deployment of data analytics in predictive maintenanceĭata analytics is an integral part of Lean Six Sigma in manufacturing as it helps to identify inefficiencies and opportunities for improvement in the production process. MAS Holdings: Using robotics and automation to reduce waste.Huawei: Using visual management boards to drive productivity.Toyota: Using Lean management to improve equipment and engage employee.Toshiba: The deployment of data analytics in predictive maintenance.With the goal of achieving process excellence by continuously improving processes, products and services to meet or exceed customer expectations, we look at the trends driving Lean Six Sigma adoption throughout the APAC region. Lean focuses on eliminating waste and maximizing customer value by streamlining processes and reducing cycle times, while Six Sigma focuses on reducing variability and defects in processes to improve quality and reduce costs. Lean Six Sigma is a management methodology that combines two distinct but complementary approaches to process improvement: Lean and Six Sigma. It is particularly well suited to manufacturing companies, however, which is why powerhouses in the APAC region are increasingly applying the principles to drive down costs and reduce waste. Lean Six Sigma methodology can be applied to any company, in any industry, around the globe.

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