The digitization of factories promises great potential benefits. The implementation of the various technologies for the smart factory is extremely complex, requires new competencies and necessitates significant investments. The question is: How can an industrial company successfully manage this transformation? For this purpose, more than 500 published use cases were screened. These could be categorized into 44 relevant use cases, which we describe in detail in the book. Our research has also shown that strategy and goal orientation must be at the core of the change. Furthermore, the combination of employee knowledge and use of technology is central to success. This led to the creation of our smart factory implementation approach. In various research and consulting projects we were able to apply this process and realize successful implementations in different companies. This 7-step process starts with the selection of promising use cases, followed by a prioritization step, adaptation to the company-specific context and a detailing of the information needs for the different management levels. Stringent project management helps the user achieve positive results that can then be rolled out on a global scale. This process is not only applicable to the "actual factory" but can also be used to design smart services for the factory of tomorrow.
Content
Smart factory definition and characterization · The smart factory navigator · The smart factory framework · Description of the 44 use cases for the smart factory · Technology mapping in relation to the 44 use cases · Smart factory implementation process · Smart services for the smart factory
Author(s): Lukas Budde, Roman Hänggi, Thomas Friedli, Adrian Rüedy
Publisher: Springer
Year: 2022
Language: English
Pages: 296
City: Cham
Preface
Contents
About the Authors
Abbreviations and Definitions
List of Figures
1 Introduction
References
2 Smart Factory Navigator
2.1 Smart Factory—The Future of Manufacturing
2.2 The Smart Factory Navigator Model
2.3 Human Centricity
2.4 Enabling Technologies
References
3 Smart Factory Framework
3.1 Structure of the Use Cases
3.1.1 Process Stage
3.1.2 Maturity Level—Degree of Analytical Foresight
3.1.3 Technology Mapping
3.2 Base Use Cases
3.2.1 Use Case 01: Data Capturing
3.2.2 Use Case 02: Data Transmission
3.2.3 Use Case 03: Data Storage
3.2.4 Use Case 04: Information Visualization
3.3 Demand Management
3.3.1 Use Case 05: Demand Diagnostics
3.3.2 Use Case 06: Demand Prediction
3.3.3 Use Case 07: Autonomous Demand Forecast
3.4 Supply Chain Management and Sourcing
3.4.1 Use Case 08: End-To-End Performance Tracking
3.4.2 Use Case 09: Marketplace Platforms
3.4.3 Use Case 10: Sustainability and Carbon Footprint Tracking
3.4.4 Use Case 11: Digital Inventory Management
3.4.5 Use Case 12: Digital Picking Assistance
3.4.6 Use Case 13: Supply Chain Early Alert System
3.4.7 Use Case 14: Supply Chain Collaboration Platforms
3.4.8 Use Case 15: Autonomous Inventory Control
3.5 Production Scheduling
3.5.1 Use Case 16: Identification and Asset Tracking
3.5.2 Use Case 17: Shift Planning
3.5.3 Use Case 18: Production Network Configuration and Coordination Assistance
3.5.4 Use Case 19: Scheduling Assistance
3.5.5 Use Case 20: Scheduling Decision Support
3.5.6 Use Case 21: Autonomous Job Scheduling
3.6 Process Optimization
3.6.1 Use Case 22: Incident Database
3.6.2 Use Case 23: Incident Pattern Recognition
3.6.3 Use Case 24: Intelligent Performance Dashboard
3.6.4 Use Case 25: Process Mining
3.6.5 Use Case 26: Digital Twin
3.6.6 Use Case 27: Process Performance Prediction
3.6.7 Use Case 28: Optimal Process Parameter Identification
3.7 Use Case 29: Autonomous Process Optimization
3.8 Process Control
3.8.1 Use Case 30: Digital Shopfloor
3.8.2 Use Case 31: Low Batch Size Manufacturing
3.9 Use Case 32: Human-Centred Flexible Automation
3.9.1 Use Case 33: Digitally Guided Operations
3.9.2 Use Case 34: Autonomously Controlled Material Flow
3.9.3 Use Case 35: Autonomously Controlled Manufacturing/Assembly
3.10 Quality Management
3.10.1 Use Case 36: Fault Detection
3.10.2 Use Case 37: Quality Diagnostics
3.10.3 Use Case 38: Quality Prediction
3.10.4 Use Case 39: Autonomous Quality Management
3.11 Maintenance
3.11.1 Use Case 40: Remote Maintenance Assistance
3.11.2 Use Case 41: Condition Monitoring
3.11.3 Use Case 42: Failure Diagnostics
3.11.4 Use Case 43: Predictive Maintenance
3.11.5 Use Case 44: Autonomous Maintenance
References
4 Smart Factory Implementation Process
4.1 Step 1: Selection of Promising Use Cases
4.2 Step 2: Classification in Potential and Complexity
4.3 Step 3: Adaption of the Use Case to a Company-Specific Context
4.4 Step 4: Creation of Personas for Each Use Case
4.5 Step 5: Project Setup
4.6 Step 6: Implementation First Project(s)
4.7 Step 7: Scaling and Internationalization
References
5 Use Case Framework to Identify Digital Services for Commercialization
5.1 DS I: Identification of Customer Value
5.2 DS II: Quantification of Customer Value
5.3 DS III: Derivation of Pricing Options
Reference
6 Learning from Case Studies and Outlook
