HORSE project is developing a methodological and technical framework for easy adaptation of robotic solutions towards SMEs to embrace the Industry 4.0 revolution to remain globally competitive. The skeleton of the framework consists of the Manufacturing Process Management System (MPMS) used to describe and control manufacturing processes, the middleware providing standardized means of communication between components, and the Hybrid Task Supervisor coordinating human operators and robots on the workcell level. MPMS is built on traditional BPM concepts (process modelling, process execution, agent allocation, task delivery, etc.) and tools. Camunda BPM is used, as a robust, open-source solution to realize MPMS.

1. Manufacturing Process
Management
(MPM)
Camunda Day
Amsterdam, 3 July 2018
Technical University of Eindhoven

2. Introduction
Kostas TRAGANOS, MSc
Business Information Systems Engineer,
Researcher
School of Industrial Engineering
Information Systems Research Group
Expertise
• Business Process Modeling
• Business Process Management
• Information Systems Architecture
• Software Development

3. 1. Project Context & Scope
2. MPM System Functionality
3. MPMS Applications (in HORSE)
4. BPM & Camunda challenges
Agenda

4. HORSE project
HORSE project (2015-2020)
• Research & innovation project
(H2020; funded by EC)
• Smart factories, Industry 4.0,
Internet-of-Things, smart
manufacturing, manufacturing
process management
• High tech manufacturing
SME’s
www.horse-project.eu
This project has received funding from the
European Union’s Horizon 2020 research and
innovation programme under grant agreement
No 680734

5. HORSE Vision
“Think of a metal factory worker manipulating and finishing a heavy
sand cast part full of sharp edges with a pair of gloves, a hammer
and a heavy grinder as only tools - and imagine how a dynamically
available robotic handling arm can improve this situation”
“Think of a car factory where human workers and robots are strictly
separated - and imagine how safe collaboration of both can make
production much more efficient”
“Think of a robotic production line where a sudden robot failure brings
things to a grinding halt - and imagine how safe human take-over of
its task can bring things up-to-speed swiftly”

6. “Smart factory” in SME’s
The challenge:
• Stay ahead of competition (Asia)
• Low volume, high variability / ‘Customized’ products
• No money for expensive information systems (e.g. ERP/MES) and
expensive technology (robots)
• Open Source solutions

7. HORSE ProjectFactory of
Future AGVs
Intrusion
detection Augmented Reality
assistance
Teaching by
demonstration
Robots

8. HORSE Project
Process management developments
• Design and enactment of manufacturing operations
• Dynamic agent allocation (with teams)
• Structured exception handling
• …
Work cell developments
• Human-robot interaction
• Augmented reality
• Situational awareness
• Teaching-by-demonstration

9. HORSE Framework

10. Scope
Reference functional hierarchy of manufacturing control (IEC, 2013)

11. HORSE Architecture (Software aspect)
HORSE Global
HORSE Local
HORSE Exec
Global
HORSE Exec
Local
HORSE Config
Local
HORSE Design
Global
Process /
Agent Data
Task / Step
/ Cell Data
HORSE Architecture [Software Aspect Level 2]
Global
Local
Design Execution

12. MPMS Functionality
• Process and Agent definition
• Runtime execution support
• Coordination and delivery of tasks
• Status and performance information
• Dynamic agent allocation to tasks
• Based on skills/abilities/availability
• Structured exception handling, e.g.
• Initiate “out-of-normal-action” process,
• Halt/resume part of the end-to-end process
• Re-assign task to human

13. Camunda BPM Community Edition!!!

14. Process Definition - Modelling
Operator Tasks
Robot Tasks
Camera Task
MPMS internal
Tasks
Human Agent
C
OPCON_Vision

15. Agent Design/Allocation
M. Arias, J. Munoz-Gama, and M. Sepúlveda, ‘Towards a Taxonomy of Human Resource Allocation
Criteria’, in 15th International Conference on Business Process Management, 2017, p. 9

16. Process Execution
In Business Domain, tasks
normally represent some
job to be done in a
computer

17. Process Execution
Exec Abstraction Layers
Global Execution
(MPMS)
Local Execution
(HTS)
Verticalintegration

18. Task – Step
Task level
Step level

19. Structured Exception Handling
Task exception
Event exception

20. MPM Funtionality
DB integration
Middleware
integration
Agent
allocation
AutoAgent
Task
Exception
handling
Exception
handling

21. Task alerting

22. Production Execution Monitoring

23. MPMS in Pilot Cases
Automated packaging of Wiper
System Assembly, including artificial
visual quality check of parts (with
augmented reality assistance), to
replace current (manual) situation

24. MPMS in Pilot Cases
Added Value
• Hybrid task allocation (robot – camera)
• Alerting
• Status monitoring

25. MPMS in Pilot Cases
• Augmented Reality assistance to
accelerate the assembling of
production tools
• Automated placing of parts on bins
and hooks

26. MPMS in Pilot Cases
Added Value
• End-to-end process overview
• Task customization
• Dynamic agent allocation

27. MPMS in Pilot Cases
• Automated cutting of metal castings
to replace current (manual) situation
• Learning by demonstration for new
castings

28. MPMS in Pilot Cases
Added Value
• “Teaching-by-Demonstration”
enactment
• Global Safety awareness scenario

29. MPM in SMEs
Future applications
• 7 new Pilot Cases

30. BPM and Camunda challenges
• BPMN
• Symbols for Robot/Hybrid Tasks?
• Pattern for “Buffers/Storages”?
• Granularity of tasks
• What is a task, what is a step
• Task delivery mechanism
• “External Task” pattern?
• “User Task” pattern?
• “Send Task” – “Receive Task” pattern?
• UI
• Customized forms in Tasklist app
• Integration to HMIs
• Cockpit functionality (Community Edition)
• More info is needed to be shown

31. Task Delivery Mechanism

32. Production Execution Monitoring
Advanced functionality with KPIs
and other info visualization

33. Kostas Traganos, MSc | Dr.ir. Irene Vanderfeesten | Jonnro Erasmus, MSc | Prof.dr.ir. Paul Grefen
Eindhoven University of Technology
School of Industrial Engineering
Information Systems group
website: http://www.horse-project.eu | contact: k.traganos@tue.nl