Manufacturing & Operational Excellence

In todays competitive and dynamic manufacturing landscape, excellence in operations is no longer optional; its a strategic imperative. The three-day Program on

Manufacturing and Operational Excellence

is a specially curated course designed to equip industry leaders and practitioners with the tools, insights, and strategic initiatives needed to transform their operations and create sustainable value. The program shall help practitioners to think from a world-class operations perspective and then align their operations decisions with the business goals to enhance competitiveness and customer satisfaction.

The course Pedagogy will help participants to understand the operations decisionmaking process from a strategic perspective. The program will also discuss data-driven decision-making, process optimization, and predictive capabilities through machine learning to enable real-time visibility in reducing waste (downtime, movement, defects, inventory) and supporting continuous improvement to promote lean, agile, and datainformed operations to achieve Operational Excellence. Thus, this program bridges the gap between traditional manufacturing practices and digital transformation, empowering professionals to lead organizational operational excellence initiatives. The hands-on session will further enhance the understanding and confidence for operational excellence.

The course will employ a mix of lectures, case studies, class, and group discussions. Through real-life cases, participants will understand the operational decisions and how they evolve in response to customer requirements.

Day 1:

Concept and need of Operations Strategy, Aligning operations with strategy. The concept of world-class operations and its management, operations improvement through Industrial Engineering tools and techniques like Muda, bottleneck analysis, SMED, OEE, Standardized Work, Takt Time, small batch size, methods improvement, and work measurement. Process analysis with cycle time, takt time, bottleneck, capacity, and throughput.

Day 2:

Overview of Quality Management Systems, digitalization of quality processes, Statistical Quality Control and data analytics, data visualization dashboards for shopfloor decision-making, evolution from classical TPM to digital TPM, IoT-based predictive maintenance, Six Sigma tools and DMAIC, machine learning-based quality control, agile manufacturing, and benchmarking for operational excellence and best practice.

Day 3:

Factory Analytics: Time Series Analysis - Machine performance; Machine Learning: Predictive maintenance forecasting; Remaining useful life (RUL); analyzing Man-machine movement. Factory Simulations and Digital Twins

:

Manufacturing process simulations and digital twins using Flexism, Anylogistix, Excel, Matlab, and Python

Objectives:

Enhance Strategic Thinking: Equip industry executives with a strategic approach to align operational goals with the overall business objectives.

Promote Operational Efficiency: Enable participants to identify and implement best practices for optimizing quality, efficiency, and effectiveness and, hence, an organizations competitiveness.

Drive Driven Decision Making: Foster the ability to apply emerging tools and technologies for waste elimination and better decision making.

A hands-on session with tools like Flexsim, Anylogistix, Excel, Matlab, And Python for better insights into decision-making tools.

The course will employ a mix of lectures, case studies, class, and group discussions. Through real-life cases, participants will understand the operational decisions and how they evolve in response to customer requirements.