Real-time Simulation for Sustainable Production: Enhancing User Experience and Creating Business Value

Cover
Half Title
Series Information
Title Page
Copyright Page
Table of Contents
Illustrations
Contributors
1 Creating Value with Sustainable Production Based on Real-Time Simulation
	1.1 Introduction
	1.2 Reflections on Sustainable Production Based on real-Time Simulation
	1.3 Origins of the Book
	1.4 Future Research Directions
	1.5 Conclusion
	References
Part I Industrial Needs of Sustainable Production
	2 Identifying Industrial Needs for Real-Time Simulation and Digital Twins
		2.1 Introduction
		2.2 Real-Time Simulation and Digital Twins Over the Product Lifecycle
			2.2.1 Real-Time Simulation and Digital Twins
			2.2.2 Product-Service System and Product Lifecycle Management
		2.3 Methodology
		2.4 Results – Identified Industrial Needs For Real-Time Simulation and Digital Twins
		2.5 Conclusions
		Acknowledgments
		References
	3 Company Capabilities and Implementing Real-Time Activities
		3.1 Introduction
		3.2 Theoretical Framework and Research Model
			3.2.1 Theoretical Framework
				3.2.1.1 Digital Business Strategy
				3.2.1.2 Digital Capabilities
				3.2.1.3 Digital Business Strategy and Real-Time Activities
				3.2.1.4 Digital Capabilities and Real-Time Activities
			3.2.2 Research Model
		3.3 Empirical Examination of Real-Time Simulation
			3.3.1 Data Collection and Sample
			3.3.2 Descriptive Results
			3.3.3 Statistical Analysis Results
		3.4 Conclusions
			3.4.1 Theoretical Implications
			3.4.2 Managerial Implications
			3.4.3 Limitations and Further Research
		References
	4 Real-Time Simulation Strategies: Implications For Operational Excellence and Sustainability Performance
		4.1 Introduction
		4.2 Real-Time Simulation For Sustainability
			4.2.1 Characteristics of Real-Time Simulation Models
			4.2.2 The Concept of Sustainability Performance
		4.3 Empirical Examination of Real-Time Simulation Strategies
			4.3.1 Data Collection
			4.3.2 Cluster Analysis Results
			4.3.3 Characteristics of the Real-Time Simulation Strategies
				4.3.3.1 The “Data Wisdom” Strategy
				4.3.3.2 The “in the Game” Strategy
				4.3.3.3 The “Bystander” Strategy
		4.4 Conclusions: Sustainable Strategies For Real-Time Simulation
			4.4.1 Theoretical Implications
			4.4.2 Managerial Implications
			4.4.3 Limitations and Further Research Directions
		References
	5 Selling Digital Twins in Business-To-Business Markets
		5.1 Introduction
		5.2 Theoretical Background
			5.2.1 Digital Twins in Manufacturing Industry
			5.2.2 Selling Data-Based Solutions in Data-Based-Business-To-Business Markets
		5.3 Research Methodology
		5.4 Results
			5.4.1 Model Illustrating the Level of Customer and Digital-Twin understanding Needed From the Sales Perspective
			5.4.2 Challenges in Selling Digital Twins
		5.5 Conclusions
		Acknowledgments
		References
Part II Game-Like Virtual Environments
	6 Accelerating Design Processes Using Data-Driven Models
		6.1 Introduction
		6.2 Concept of a Data-Driven Model
			6.2.1 System Modeling
			6.2.2 Neural-Networks-Based Data Models and Other Methods
			6.2.3 Data-Driven Models in the Multibody Framework
		6.3 Applications of Data-Driven Models
			6.3.1 Research and Product Development
			6.3.2 Enhanced Operation
			6.3.3 Maintenance and Service
			6.3.4 New Business Opportunities
			6.3.5 Supporting Sales and Purchase
		6.4 Conclusions
		Notes
		References
	7 Gamification and the Marketing of Agricultural Machinery
		7.1 Introduction
		7.2 Modeling An Agricultural Machine
			7.2.1 Design Process For Parameterization
			7.2.2 Environment Modeling
		7.3 Gamification
			7.3.1 Elements of a Game
			7.3.2 Methods of Data Extraction
		7.4 Case Example of a Farm Tractor
			7.4.1 Gamification of the Farm Tractor Model
			7.4.2 Product Development Opportunity
			7.4.3 Marketing Opportunity
		7.5 Conclusion
		Acknowledgment(s)
		References
	8 Added Value From Virtual Sensors
		8.1 Introduction
		8.2 Virtual Sensors: Context and Background
		8.3 Virtual Sensors As a Part of the Product Offering
			8.3.1 Technical Methods Enabling Virtual Sensing
				8.3.1.1 Analytical Methods
				8.3.1.2 Numerical Methods
			8.3.2 Opportunities/benefits and Challenges of Virtual Measurements
				8.3.2.1 Offline Virtual Measurement – Slower Than Real Time
				8.3.2.2 Online Virtual Measurement – Faster Than Real Time
			8.3.3 Business Opportunities Introduced By Virtual Sensors
		8.4 Conclusions
		References
	9 The Technical-Business Aspects of Two Technical-Business-Mid-Sized Manufacturing Companies Implementing a Joint Simulation Model
		9.1 Introduction
		9.2 Related Research
		9.3 Methodology: Assembling the Joint Simulation Models
			9.3.1 Developing Customer-Oriented B2B Products
			9.3.2 Preparation of B2B Parameterized Real-Time Joint Simulation Model
			9.3.3 Combining Parameterized Models and the Optimized Model
		9.4 Joint Simulation of Industrial Mobile Machines
			9.4.1 Technical-Business Challenges of Joint Simulation/Joint simulation Challenges
			9.4.2 Real-Time Joint Simulation Solutions
				9.4.2.1 Selection of Optimal Parameters
				9.4.2.2 Optimal Range of Parameters
				9.4.2.3 Joint-Model Stability
				9.4.2.4 Feasibilities of Joint Simulation Combinations
				9.4.2.5 User Selection of Parameterized Model/User Designing and Testing of Simulation Model
			9.4.3 Collaboration Benefits and Issues On the Alliance
		9.5 Conclusions
		References
Part III Capturing Customer Value and User Experience
	10 Implementing Digital Twins to Enhance Digitally Extended Product-Service Systems
		10.1 Introduction
		10.2 Related Research
		10.3 Research Methodology
		10.4 Results
		10.5 Discussion and Conclusions
		Acknowledgments
		References
	11 The Expected Benefits of Utilizing Simulation in Manufacturing Companies: Insights From a Delphi Study
		11.1 Introduction
		11.2 Simulation Modeling Motives in Manufacturing
		11.3 Research Method and Data Gathering Process
		11.4 Simulation Modeling in Manufacturing Companies: Insights From the Expert Panel
			11.4.1 Benefits of Using Simulation in the Long Term For the Customer and Other Stakeholders
			11.4.2 The Business-Activity Related Effects of Simulation
		11.5 Conclusions
		References
	12 Integrating the User Experience Throughout the Product Lifecycle With Real-Time Real-Time-Simulation-Based Digital Twins
		12.1 Introduction
		12.2 Related Research
			12.2.1 Multibody Definition of a Digital Twin
			12.2.2 Product Lifecycle
			12.2.3 The User Experience
			12.2.4 Co-Creating Product Value With the UX and Co-Creating-Multibody-Based digital Twins
		12.3 Enabling User Experiences in the Product Lifecycle With An Immersive Multibody-Based Multibody-Based-Digital-Twin Approach
			12.3.1 Developing a User-Centered Virtual Space of a Physical Model
			12.3.2 User Selection of Component Design Data
			12.3.3 Immersive Methods For Generating User Input
			12.3.4 Simulator Or Motion Feedback Platform
			12.3.5 VR, AR, Mixed Reality Glasses, Leap Controllers and Haptics
			12.3.6 Manufacturing of the Physical Product
			12.3.7 Real-Time Communication Between the Physical and Virtual Spaces of the Digital Twin
			12.3.8 Product Life Management Data
			12.3.9 Enhancement of Measured Data
		12.4 Industrial Case Study: the UX in Different Phases of the Product Lifecycle With a Multibody Digital Twin
			12.4.1 New Product Development Approach: User Co-Creation of a New Forklift Mast System in the Virtual Space
			12.4.2 Commercialization: User Testing of the Parameterized Model in Different Environments
			12.4.3 Manufacturing: Utilizing the User-Based Multibody Model in Production
			12.4.4 User-Related Product Services in the Operation Phase: Updating the Virtual Space of the Digital Twin With User-Related-Real-World Information
			12.4.5 End of Product Life: Retiring the Product Based On User Data generated in the Digital Twin
		12.5 Conclusion
		Acknowledgments
		References
Part IV Value for Business
	13 The Digital Twin Combined With Real-Time Performance Measurement in Lean Manufacturing
		13.1 Introduction
		13.2 Context and Background
			13.2.1 Lean Approach and Performance Measurement
			13.2.2 Digital Twins and Performance Measurement
		13.3 Methodology
		13.4 Advantages of the Digital Twin and Real-Time Performance Measurement
			13.4.1 Advantages to Stakeholders
				13.4.1.1 Management
				13.4.1.2 Worker
				13.4.1.3 Customer
			13.4.2 Advantages By Process Perspective
		13.5 Conclusion
		References
	14 Using Real-Time Simulation in Company Value Chains and Business Models For Value Creation
		14.1 Introduction
		14.2 The Effect of Digitalization On the Market
		14.3 Real-Time Simulation Models and How They Create Value For Customers
		14.4 Business Model Canvas As a Tool to Analyze the Value Chain
		14.5 Applying Real-Time Simulation to Different Alue Chain Activities
			14.5.1 Applying Real-Time Simulators in R&d and Product Development
			14.5.2 Applying Real-Time Simulators in Training
			14.5.3 Applying Real-Time Simulators to Predict Faults
			14.5.4 Applying Real-Time Simulators in Services
			14.5.5 Applying Real-Time Simulators in Sales and Marketing
			14.5.6 The Effect of Real-Time Simulation On Business Models
		14.6 Discussion and Conclusions
		Notes
		References
	15 Sustainable Competitive Advantage Through the Implementation of a Digital Twin
		15.1 Introduction
		15.2 A Multidimensional Model For the Implementation of a Digital Twin
			15.2.1 Theoretical Underpinnings
			15.2.2 Defining a Digital Twin
			15.2.3 Description of the Model
				15.2.3.1 Firm Competencies
				15.2.3.2 Strategic Direction
				15.2.3.3 Sustainability Performance
				15.2.3.4 External Environment
		15.3 Requisite Competencies and Research Propositions
			15.3.1 Linking Competencies to the Strategic Direction of a Digital Twin
			15.3.2 Linking Strategic Direction of a Digital Twin to Sustainability performance
			15.3.3 External Environment As Moderator
		15.4 Conclusions
			15.4.1 Theoretical Implications
			15.4.2 Managerial Implications
			15.4.3 Limitations and Further Research Directions
		References
	16 Managing Digital-Twin lifecycle – Recognition and handling of Business Risks
		16.1 Introduction
		16.2 Theoretical Background
			16.2.1 Digital Twins
			16.2.2 Digital Twin Lifecycle
			16.2.3 Lifecycle Risks of Digital Twins
		16.3 Research Methodology
		16.4 Results
		16.5 Concluding Remarks
		Acknowledgments
		References
Index