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Instructor

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Su Doyle

Su Doyle has been an Internet of Things adviser to Manufacturing, Supply Chain and Retail leaders since 2007.  She has authored over 50 articles and best practices guides on Sensor-enabled Process Automation.  Her experience includes working with IoT enterprise platform and hardware firms OATSystems, Microsoft, Tego and Xerafy as well as Product Management leadership roles with Vovici, Providus, Engage and Lycos.

Smart Manufacturing: The Connected Factory

Instructor: Su Doyle

How IoT sensors transform assembly, asset management & aftermarket processes

  • Instructor's experience includes working with IoT enterprise platform and hardware firms OATSystems, Microsoft, Tego and Xerafy as well as Product Management leadership roles with Vovici, Providus, Engage and Lycos.
  • Learn how IoT sensors, automation, and data science are transforming individual processes and improving operational performance throughout the manufacturing enterprise. 

Course Description

This course provides a detailed “before and after” walk-through of a manufacturing operation (from component sourcing to final assembly and aftermarket services) with the implementation of IIoT / IoT sensors, process automation and advanced analytics. Best practices for adapting use cases for high-complexity, high regulation and high-velocity environments are also discussed, along with industry benchmarks to help prioritize areas best suited for sensor deployment.

What am I going to get from this course?
Detailed understanding of how IoT sensors, automation and data science are transforming individual processes and improving operational performance throughout the manufacturing enterprise.  Evaluation criteria and industry benchmarks for determining where and how smart manufacturing processes can benefit your organization.

Prerequisites and Target Audience

What will students need to know or do before starting this course?
Familiarity with manufacturing and logistics processes and systems. 
Who should take this course? Who should not?
Business leaders and program managers in manufacturing organizations.  Technology suppliers for Manufacturing, Warehousing and Asset Management.   

Curriculum

Module 1: Overview
Lecture 1 What is a Connected Factory?

This lecture explains the different aspects of a connected factory including definitions of Smart Manufacturing, Industry 4.0, the IIoT (Industrial Internet of Things) and the IoT (Internet of Things) along with why the stage has been set for manufacturers to run leverage sensors, automation and data science to run a digital business. It also includes a quick primer of underlying technologies and a brief survey of how manufacturing CEOs are investing in new capabilities.

Lecture 2 Digitization and the Manufacturing Enterprise

An overview of Smart Manufacturing use cases from within the four walls of a manufacturing facility to global supply chains and aftermarket services, from both a brownfield and greenfield perspective. Use Cases are mapped to specific business challenges (tooling proliferation, aftermarket service, regulatory pressure) and new manufacturing technologies, such as advanced composites and additive manufacturing. A brief overview of industry-specific use cases of connected factories is included.

Lecture 3 Criteria for Connected Factories

What are the most common reasons for adopting sensors in manufacturing operations? Which manufacturing industries and processes stand to benefit most? Includes an example of an aerospace manufacturer who sensor-enabled work-in-process tracking and supply chain operations for a new aircraft program.

Module 2: Within the Four Walls of a Factory
Lecture 4 Leveraging Sensors on the Factory Floor

Applying Smart Manufacturing to Assembly Processes (Discrete, Process, Advanced Materials & Additive Manufacturing) with underlying technology options and “Before and After” Process Flows.

Lecture 5 Customer Order Management

Providing transparency to end customers by tracking order status at each step of a complex assembly process.

Lecture 6 Managing Component Inventory

Using sensor technology to track serialized and non-serialized components as they are received, warehoused and used to construct sub-assemblies and finished goods.

Lecture 7 Materials Management

Using sensors to track material inventory (including high-value, high-risk and perishable material) used in the manufacturing process.

Lecture 8 Sensors at the Dock Door

Using sensors to automate Inbound Receiving, Putaway and Shipping processes.

Module 3: Manufacturing Across Multiple Facilities
Lecture 9 Inter-facility Shipment Tracking

Automating shipment confirmation and verifying contents of shipping manifests. Issuing accurate Advanced Shipping Notifications (ASNs) and customs documentation for international shipments.

Lecture 10 Managing Capital Assets

Discussing the impact of capital assets on a manufacturer's balance sheet and how Digital Asset Management can improve asset utilization.

Lecture 11 Managing Indirect Materials

Tracking inventory location and maintenance status of tooling, transport jigs and specialized materials (such as those used for composites fabrication processes) to reduce the risk of quality issues and the cost of excess inventory.

Lecture 12 Final Assembly Processes

Automating the final stages of manufacturing complex goods upon documentation, audit and delivery to the end customer.

Module 4: Managing the Product Lifecycle
Lecture 13 Sensor-enabled Supplier Networks

Collecting sensor data from the point of manufacture by bringing component suppliers and service partners (including 3PLs) into the fold. Includes best practices for supplier programs that benefit both parties.

Lecture 14 Sensors in Aftermarket Services

Using sensor technology to improve quality of service and reverse logistics once the finished product is in the hands of the customer. Using "digital twins" as well as adding smart capabilities to products that provide predictive maintenance and help minimize downtime.

Module 5: Best Practices
Lecture 15 Integrating with Enterprise Systems of Record

Informing ERP, WMS, PLM, MRO & MMS systems and other systems of record with sensor data to improve efficiency and reduce implementation time. Using sensor data as a “common denominator” for disparate systems.

Lecture 16 Adding Sensors to Existing Machinery

Instrumenting legacy equipment and processes with plug-and-play sensors to monitor assets, energy use and to provide documentation at point of use.

Lecture 17 Connected Factories in the Cloud

Evaluating IoT offerings from cloud vendors and considerations for hybrid and on-premise deployments.

Lecture 18 Sensor Data Management

Understanding what types of data are required for real-time decisions and for future analysis. Examples of using sensor data for alerts, dashboards, analytics and machine learning will also be discussed.

Lecture 19 Making the Business Case for a Connected Factory

Understanding C-Level priorities by functional area to build support for a Smart Manufacturing Initiative. Evaluating industry benchmarks for material costs, asset utilization, customer satisfaction and other KPIs to quantify and prioritize where Smart Manufacturing will make the most impact.

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