Deloitte Smart Factory Fabric Solution

Accelerating Smart Factory Transformations for Companies with Manufacturing Operations

Background

Digital has transformed manufacturing over the past decade. The Cloud and Internet of Things (IoT) have helped companies make gains in efficiency and productivity that are nothing short of revolutionary. But, the revolution isn't over. For companies with complex manufacturing operations, implementing a smart factory solution at industrial scale can be daunting, but critical for those who wish to remain competitive today.

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Version: 1.0
Last updated: 7/2020
Author: AWS 

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Overview

Smart Factory Fabric is a pre-configured suite of cloud-based IoT applications designed to accelerate smart factory transformations for companies with manufacturing operations. Powered by AWS IoT, Deloitte designed and built a suite of cloud applications and integrated services to deliver smart factory capabilities to industrial enterprises. The Smart Factory Fabric suite of services helps companies improve their operational performance and reduce costs by increasing visibility, improving production, improving quality, and reducing unplanned downtime associated with running a smart factory.

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Benefits

Smart factory transformations, when done at the plant or enterprise level, can help create significant cost savings, improve product quality, and increase employee satisfaction.

Improve Asset Efficiency

  • Optimize capacity and asset utilization
  • Decrease changeover time and downtime

Improve Process Efficiency

  • Decrease scrap rates and lead times
  • Increase fill rate and yield

Reduce Costs

  • Lower labor, sourcing, inventory, maintenance, and warranty costs

Improve Safety and Sustainability

  • Decrease safety incidents and environmental impact
  • Increase employee satisfaction and sustainability practices

Features

Asset Track and Trace
Dynamically track work orders and parts through defined routes and optimize against work order schedules based on constraints (part, machine, or resource).

Machine Monitoring
Capture, analyze, and display critical machine performance data that allows operators to know machine status, receive proactive alerts and notifications, and improve overall equipment efficiency (OEE) performance.

Command Center
Drive the optimization of overall factory network capacity by providing a command center to visualize asset performance and cross-factory utilization.

Predictive Maintenance
Cloud-based and Edge-deployed AI/ML algorithms that are able to proactively sense and detect operating conditions that result in catastrophic failure upon deployment without the maintenance team having to build a knowledge base.

Quality Sensing
AI/ML algorithms that are able to proactively sense and detect quality degradation issues with the goal of catching quality escapes earlier in the process.

Advanced Worker Solutions
Align available workforce resources to production needs dynamically, allowing supervisors to manage and optimize for constraints, and view performance in real time.

Dynamic Scheduling
Interactive, real-time solutions that allows operations management to proactively identify issues where the current production schedule is inconsistent with the output capabilities of the asset(s) in the production.