BIOGRAPHY

Satya Kudapa

SM COE Leader & Trusted Business Advisor, TMAC, Arlington, TX, USA


Satya Kudapa has more than 18 years of experience providing professional consulting, mentoring and project management support to businesses in the Dallas-Fort worth Area. His experience spans to a wide variety of industry clusters including medical, aerospace, utilities, fabrication and city governance. Over the years, Satya has worked with numerous TMAC customers in varying capacities as a lead Project Manager and Trusted Business Advisor assisting with the design & development of Quality Management Systems, applying Lean Management Principles, and deploying Lean Six Sigma Programs.Satya currently leads TMAC’s statewide Smart Manufacturing Center of Excellence (COE) which is critical to the development of its Industry 4.0 related products and services, developing center capabilities and providing program and grant management support. He also supports the Cyber Security team at TMAC that is responsible for the development of cyber related products and capabilities (DFARS 7012, NIST 800-171 & CMMC).Satya holds a Master of Science degree in Industry and Management Systems Engineering from The University of Texas at Arlington. Satya is also a certified Lean Six Sigma Master Black Belt.

ABSTRACT

The Evolution of Lean Six Sigma Through Sensorization, Data Visualization, and Industry 4.0

The Lean Six Sigma methodology has been successfully applied for over 20 years in a wide variety of industries. A challenge from the beginning has been getting good data, whether it be for process inputs or outputs. Increasingly LSS practitioners are overcoming this challenge through the use of sensors for data collection. The costs of sensors have plummeted over the past decade, while the complexity of the data they can record has increased. Parallel to the growth of sensors is the expansion of cloud computing which has provided a ready resource for expanded data storage and retrieval.How can sensors, cloud computing, and data visualization be leveraged to enhance the successful application of the DMAIC process? Where in the DMAIC process should sensors be applied? How should LSS practitioners adapt the use of traditional tools and methods such as control charts to real-time data and dashboards, especially when the volume of data increases by several orders of magnitude? These questions and more will be addressed in this presentation. In addition, a case study will be shared to show how basic sensors were used with data visualization to solve a quality problem in a beverage industry application.


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