digital ecosystem Flashcards
What is an ecosystem?
includes a platform that serves as a core on which others can build modules that are designed to extend the service possibilities of the platform.
includes various social actors who build the platform and various modules and a regulatory regime including standards that bind these heterogeneous actors together
taxonomy
Taxonomy is the practice and science of classification.
key drivers in industry 4.0
predictive maintanance
- reduction of maintenance costs of factory equipment by 10-40%
- reduction of equipment downtime by up to 50% •reduction of equipment capital investment by 3-5% •potential economic impact of nearly $630 billion p.a. in 2025
maintenance
preventiv vs corrective
preventive
- predeterminded
- condition based
Condition based
- predictive
maintenance scenarios
Sequential procedure for the evaluation
(1) selection of a machine or production line
(2) identification of failure and cause
(3) capture or simulation of sensor data
(4) selection and training of machine learning algorithms
(5) calculation of maintenance cost and scenarios
(6) Decision on sensors, algorithms, strategies
relevant points that control a market
- traditionally IDEP
- new comers UC, DA ,PE
traditional: IDEP Intellectual property Distribution network Expertise Production capacity
new comers: UC, DA, PE
1. User / Client:
connection to customer creates lock-in effect - improves validated learning
- Data and analysis
Typically own detailed data will support Advanced analytics to obtain valid/sound knowledge (e.g. regarding clients‘ behavior - Platform and ecosystem
enables interaction between the clients and third parties
to generate quick multiplier- and scale-effects
self-reinforcing system
along the three digital control points
- strong emphasize on DATA
- ECOSYSTEM around platform
successful digital business proposition with strong emphasis on data
digital champions succeeded in building an ecosystem around platform
MindSphere
open cloud platform or “IoT operating system” developed by Siemens
for applications in the context of the Internet of Things.
stores operational data and makes it accessible through digital applications to allow industrial customers to make decisions based on valuable factual information.
Micro
Meso
Macro
Perspective
- sociologists examine the smallest levels of interaction; even in some cases, just “the self” alone. Microlevel analyses might include one-on-one interactions between couples or friends
- psociologists tend to study the experiences of groups and the interactions between groups
- macro level research study interactions at the broadest level, such as interactions between nations or comparisons across nations
target of ecosystems
specific domain - bringing supply side, demand side, players and information together in one dedicated place so that information does not remain fragmented and products and solutions can be readily identified and procured
Key capabilities for industry 4.0
Smart data management
3 Horizons of industry 4.0
https://www2.deloitte.com/insights/us/en/focus/industry-4-0/building-capabilities-through-collaborations-startups.html
initial phase: initial connectivity
- Process optimization
- Process flow and quality
- New business models
Industry 4.0
is a state in which manufacturing systems and the objects they create are not simply connected, drawing physical information into the digital realm, but also communicate, analyze, and use that information to drive further intelligent action back in the physical world to execute a physical-to-digital-to-physical transition
Industry 4.0
economic value
Reduced time to market
Cost reduction
Sales increase
Extended production phase
Industry 4.0
Components and technologies
- embeded systems CPS (A cyber-physical system is a mechanism that is controlled or monitored by computer-based algorithms, tightly integrated with the Internet and its users)
- Smart factory
- robust network
- cloud computing
- It security
Transformation Management
Challenges
Challenges:
Redefine the roles of the CIO and the IT department. Identify sponsor of digital transformation
define a Leader!
IT need to become an enabler
Traditionally viewed as cost driver and hygiene factor
• business & customer perspective becomes more important for IT
Transformation Management
possible approach
• Role and responsibility of the IT department • Internal service provider? • Equal partner? • Driver of digital transformation? • Novel interfaces to other business units • Cross-disciplinary teams • New skill profiles
Basic principles of Industrial Data Space (IDS)
Data owners define the terms of use of their data and „staple“ these on their data commodities. Digital Sovereignity
Data can be – if required – managed peripherally by the data owner. Federal Data Management
Data is a commodity and can be subdivided into private and public data commodities. Data Economy
Industrial Data Space enables smart services as well as data-centered digital business models. Wealth Creation
Linked data concepts and common vocabulary simplify data integration between IDS participants. Easy Data Linking
Members of IDS, data sources and data services are certified against colectively established rules. Legitimate Expectation
Data exchange is safe along the data wealth-creating chain, from the data creation until their use. Safe Data Supply Chain
Data management processes and IDS members rights/duties are set jointly by the operator
