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Quick Facts

Medium Of InstructionsMode Of LearningMode Of Delivery
EnglishSelf Study, Virtual ClassroomVideo and Text Based

Courses and Certificate Fees

Certificate AvailabilityCertificate Providing Authority
yesIIM Visakhapatnam

The Syllabus

Smart Operations Management
  • Smart Operations Processes Design and Analysis
  • Smart outsourcing and plant production
  • Analytical tool for assessing smart operations (ordering, production scheduling,and quality monitoring)
  • Digital Service Operations planning and execution
  • Value of information and value chain analysis
  • Manufacturing and service operations system design and analysis
Smart Manufacturing Strategy
  • Introduction to Operations Strategy
  • Defining Smart Manufacturing
  • Framework for Manufacturing 4.x
Logistics- 4.0
  • Logistical strategy formulation and logistical capabilities assessment
  • Logistical capability mapping (technology readiness mapping)
  • Logistical integration (vertical and horizontal), collaboration, and coordination analysis
  • Freight distribution cluster design, and hyper-local logistics system design
  • Smart facilities (warehouse) management, digital control of warehouse
Managing Digital Operations for Circular Economy
  • Introduction to Sustainable Digital Operations
  • Multiple Objectives
  • Framework for implementing Sustainable Operations
  • Circular Economy (CE) - Overview
  • Evolution of the concept
  • CE-A Generic Framework
Digital Leadership (Managing Modern Enterprices)
  • Understanding Modern Enterprise
  • Digital Leadership in 'VUCA World'
  • Managing Enterprise Content
  • Foresight, Enterprise Policies and for Digital Leadership

Exploring the Data Analytics and its Maturity models
  • Maturity Model#1 with respect to Human-Decision-Action.
  • Maturity Model#2 with Complexity vs. Value addition.
  • Descriptive Analytics and Diagnostic Analytics with their case studies. Confusion matrix
  • Predictive Analytics and Prescriptive Analytics with their case studies. Sensitivity Analysis for estimating the influence of parameters on the outcome.
Exploration of AI and ML techniques
  • Introduction to Machine Learning and AI
  • Regression techniques
  • Classification techniques
  • Clustering techniques
  • Applications in Manufacturing

Maturity Model of Automation and Industrial Robotics
  • Maturity Model of Automation. Case study for each level of automation.
  • Relation between Industry4.0 – Operator 4.0 – Automation levels.
  • Types of Robotic Operations; Hardware and Software based Robots;applications in process automation for Smart Manufacturing.
  • Robot Motion Analysis and Control;
  • Robot Peripherals: End Effectors, Sensors, Actuators
Robot Cell Design Process and Autonomicity
  • Robot Cell Design and Control
  • Introducing Intelligence into the Robots
  • Machine Vision and Robotic Operations;
  • Cobots and Dobots
Strategic Analysis of various forms of applications of Robotics
  • Economic Analysis for Robotics
  • Implementation Principles and Issues
  • Robot Applications in Manufacturing: Material Transfer; Processing Operations; Assembly and Inspection;
  • Social Issues and Future of Robotics.

Cloud Computing models; Virtualization; Load Balancing methods
  • Introduction to cloud computing 
  • Cloud issues and challenges 
  • Virtualization and Load balancing 
Cloud service and platforms
  • Commercial clouds 
  • Open source private clouds
Applications using IoT and Cloud Computing
  • Ubiquitous Cloud and IIoT 
  • Cloud Application in Mass Customization.

Design for Additive Manufacturing

Laser Power bed fusion of metals
  • Input Data Processing and Build File Preparation
  • Architecture of Laser Powder Bed Fusion System and Complete Process Chain
  • Post Processing of Additive Manufactured (AM) Parts
  • Testing and Certification of AM Parts
  • Applications – Aerospace, Defence, Energy, Oil & Gas Sectors
Industrial Iot and Polymer 3D printing
  • Vat Polymerisation, Extrusion Technology and Multijet Processes 
  • Industrial Case Studies – Medical Devices and White Goods 
  • Industrial IoT for 3D Printing
Additive Manufacturing Materials
  • Characterisation of Additive Manufactured Materials
  • Optimising The Process Parameters for maximising the throughput and quality
  • Adapting New Materials to Extend Applications 
Design for Additive Manufacturing
  • Reducing the part count and making unibody parts 
  • Mass Customisation 
  • Reengineering and reconfiguring supply chains

Instructors

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