Outthink Complexity with Industrie 4.0 Pilot Project at John Deere Werk Mannheim, Germany

Transcription

1 Outthink Complexity with Industrie 4.0 Pilot Project at John Deere Werk Mannheim, Germany 2016, April Pilot Project Partnership

2 Demo Case Summary John Deere, IBM, technology solution providers and research institutes started the realization of Industrie 4.0 use cases as a joint effort in two pilot areas Exploring the potential of Industrie 4.0 technologies combined with the lean production approach already established The solution architecture is based on the IBM Industrie 4.0 integration platform, supported by best-in-class partner technologies and experience Enabling flexible application integration and production data exchange Fostering close collaboration and interaction of employees, process & order data, machines and sensors Building a foundation for the deployment to further manufacturing processes 2

3 Smart Factory a Combination of Lean Production and Industry 4.0 / Industrial Internet Principles Today s Challenges: High/increasing number of product variants, increasing complexity Fluctuating customer demand Shorter product life cycles Management of supply chain Lean Production Efficient Material Flow Elimination of non-value-adding activities Kanban Processes Low WIP inventories + Industry 4.0 / Industrial Internet Efficient information flow Elimination of data redundancies (data as intangible assets ) Decentralized, self-controlled Systems & processes (via new enabler technologies) 3

4 LX Industry 4.0 Pilot Fast Prototype First Implemented Use Cases I4.0/IoT John Deere Mannheim Use Case 1/3: Digital Build Paper Use Case 2/3: Worker Assistance Use Case 3/3: Sense & Act 4

5 LX Industry 4.0 Pilot Fast Prototype Use Case 1/3: Digital Build Paper Solution Electronic Build Paper (system integration) System-based order planning Automated order identification Automated handover of order data to pick-to-light system Feedback via pick-to-light (IO/nIO) Kitting tablet controls manufacturing process Technology RFID order identification CPS: sensor data (RFID tag) Integration platform (data hub) Worker assistance system (electronic build paper) 5

6 LX Industry 4.0 Pilot Fast Prototype Use Case 2/3: Worker Assistance System Solution Employee identification via ID card Worker guidance via step-by-step visualization of work instructions Qualification directly at the workplace Online feedback possible Additional information provided via integration of Wearables Integration of automated fault detection Automated triggering of work instructions via RFID Option: Workplace-specific configuration of screen masks Technology Smart Cards (worker identification) Assistance System (system-based worker guidance) RFID (triggering of work descriptions) Integration Platform 6

7 LX Industry 4.0 Pilot Fast Prototype Use Case 3/3: Sense & Act Solution ERP MES Order identification via RFID antenna Interconnection between machines/devices and shop floor systems via CPS Integration platform as data hub Application-independent definition of rules (not hard-coded) Rule set can be applied down to device level Technology RFID / RTLS (identification und localization) CPS (Transfer of sensor data, e.g. RFID tag, machine condition) Integration platform (data hub) Application-independent rule engine (native rules definition) 7

8 Demonstration Use Case 2, Worker Assistance System

9 Mobile App/Solution Interconnected with Worker Assistance System Solution: Reporting of identified failures via worker assistance system (W.A.S.) as a service request Maintenance staff member assigns to specific failure(s) and starts maintenance work Feedback is given to the worker at the relevant station(s) via W.A.S. If maintenance staff member arrives at the machine/station, the app is able to recognize the machine via image recognition The app contains a knowledge dialog based on Cognitive Computing connectivity [e.g. WATSON] to support failure analysis The app also contains appropriate connectivity for the communication with the related supervisor or other experts supporting the affected machine/equipment/tool 9

10 in the SMP Architecture Multiple Cloud Services (Cognitive Computing, Speech to Text, etc.) Potential Problem Alert Worker Assistance System Integration Platform Smart Manufacturing Bus Powered by: Image Recognition and Maintenance Dialog Application Powered by: 10

11 Used Bluemix Services Node.js Push Notification Watson Speech to Text Watson Retrieve and Rank Watson Text to Speech Watson Visual Recognition Watson Dialog 11

12 Demonstration Use Case 3, Sense & Act Every Hour Here at the Work Station

13 Project Collaboration & Pilot Partner Responsibilities DFKI / SmartFactory KL Knowledge Sharing I 4.0 Experiences IBM Integration Bus Rules Management Armbruster Hilscher Pick-by-Light Automated Commissioning BridgingIT netiot / Cyber-Physical System DE software & control Mobile App Development Agile Project Methodology Worker Assistance System 13

14 SMP Pilot Functional Architecture Other systems (SAP, databases, etc.) Workflow (HMI for Worker & Planer) uses Rules (relationships) Smart Manufacturing Platform integrates integrates Shopfloor Data Model (contents) based on accesses uses Integration Layer integrates CPS (intelligent gateway) accesses Machines / Equipment 14

15 Rough IBM Product Mapping to John Deere s Smart Manufacturing Platform IBM BPM IBM Decision Server Rules for Integration Bus IBM Integration Bus Manufacturing Pack 15

16 Industrie 4.0 Architecture - Advantages Backend integration (ERP/MES, etc.) Hosting of micro services Execution of transactions with soft real-time Simple distribution of functionalities to multiple nodes Communication between components on the shop floor Easy installation, activation and change management Simplified resource management by clear & monitored communication paths Simple expandability (e.g. new protocols and processes) 16

17 17