Conference: 23rd ICE/IEEE ITMC Conference (ICE2017). Madeira, Portugal – June 27-30, 2017 Title of the paper: An Approach to Production Scheduling Optimization A Case of an Oil Lubrication and Hydraulic Systems Manufacturer Authors: Artem Katasonov, Toni Lastusilta, Timo Korvola, Leila Saari, Dan Bendas, Roberto Camp, Wael M. Mohammed, Angelica Nieto Lee if you would like to receive a reprint of the original paper, please contact us.

1. An Approach to Production Scheduling
Optimization
A Case of an Oil Lubrication and Hydraulic Systems
Manufacturer
Date: 29th of June, 2017
Contact Information
Tampere University of Technology
FAST Laboratory
P.O. Box 600,
FIN-33101 Tampere
Finland
Email: fast@tut.fi
www.tut.fi/fast
Conference: 23rd ICE/IEEE ITMC Conference
(ICE2017).
Madeira, Portugal – June 27-30, 2017
Title of the paper: An Approach to Production
Scheduling Optimization
A Case of an Oil Lubrication and Hydraulic Systems
Manufacturer
Authors: Artem Katasonov, Toni Lastusilta, Timo
Korvola, Leila Saari, Dan Bendas, Roberto Camp,
Wael M. Mohammed, Angelica Nieto Lee
if you would like to recieve a reprint of the
original paper, please contact us.

2. An Approach to Production
Scheduling Optimization
A Case of an Oil Lubrication and Hydraulic Systems
Manufacturer
23rd ICE/IEEE ITMC Conference (ICE2017).
Madeira, Portugal – June 27-30, 2017
Artem Katasonov,
Toni Lastusilta,
Timo Korvola, Leila
Saari, Dan Bendas
VTT Technical
Research Centre of
Finland Ltd
Espoo/Oulu, Finland
Roberto Camp
Fluidhouse Ltd
Jyväskylä, Finland
Wael M.
Mohammed,
Angelica Nieto Lee
Tampere University of
Technology
Tampere, Finland

3. Outline
• Introduction
• Motivation
• The case study
• The approach
• Results
• Validation of the pilot
• Conclusion and the future work
An Approach to Production Scheduling Optimization 3

4. Introduction
Fluidhouse Ltd. is a Finnish Original
Equipment Manufacturer (OEM) with over
40 years’ experience in the design,
manufacturing, and project management of
oil lubrication and hydraulic automation
systems.
Cloud Collaborative Manufacturing
Networks (C2NET) project is an EU
Horizon 2020 R&D project within the
framework of the Factories of the Future
(FoF) public-private partnership. The goal
of the project is the development of Cloud-
enabled tools for supporting SMEs supply
network optimization
http://www.fluidhouse.fi/en/
http://c2net-project.eu
An Approach to Production Scheduling Optimization 4

5. Motivation
As a partner in the C2NET project, Fluidhouse represents
the one of the industrial partners in the C2NET project.
Thus, Fluidhouse provides the project with three scenarios
in order to validate the project features.
1. Order management
2. Production management
3. Purchases management
An Approach to Production Scheduling Optimization 5

6. The Case Study
• Fluidhouse represents the manufacturer in the supply
chain.
• Supplier -> Fluidhouse (Manufacturer) -> Customer
• This case-study addresses the production management
• Order -> production plan -> purchase plan -> production
process -> shipping
An Approach to Production Scheduling Optimization 6

7. The Case Study (Problem Definition)
order
production
plan
Purchase
plan
production shipping
order
production
plan
Purchase
plan
production shipping
production
plan
production shipping
order
production
plan
production shipping
order
production
plan
Purchase
plan
production shipping
Purchase
plan
Purchase
plan
An Approach to Production Scheduling Optimization 7

8. The Case Study (Problem)
Employees skills
Employees type
Orders / projects
Employees schedules
Production plan
Fluidhouse planner
• By knowing the employees’ skills, employees’ schedules, employees’ type
and the project information, the Fluidhouse company planner is able to
create the production plan manually
• This use-case aims at supporting Fluidhouse with automated production
planning using the optimizers
An Approach to Production Scheduling Optimization 8

9. The Case Study (Solution)
Employees skills
Employees type
Orders / projects
Employees schedules
Production plan
C2NET Optimizer
• By knowing the employees’ skills, employees’ schedules, employees’ type
and the project information, the Fluidhouse company planner is able to
create the production plan manually
• This use-case aims at supporting Fluidhouse with automated production
planning using the optimizers
An Approach to Production Scheduling Optimization 9

10. The Approach (C2NET Architecture)
The used components are highlighted in red rectangles
An Approach to Production Scheduling Optimization 10

11. The Approach (optimization algorithm)
• Mixed-Integer Linear Programming
(MILP) model for the scheduling of
production and human resource.
• distributes the work load of
production operations among
available workers, matching their
skills.
• Model features:
• It treats delivery dates as hard
constraints, no late deliveries
are allowed.
• It allows overtime / hiring
temporary external workers
• As the primary sub-objective, it
minimizes such
overtime/external hire cost.
Model Input
An Approach to Production Scheduling Optimization 11

12. The Approach (optimization algorithm)
An Approach to Production Scheduling Optimization 12

13. The Approach (optimization algorithm)
An Approach to Production Scheduling Optimization 13

14. The Approach (optimization algorithm)
An Approach to Production Scheduling Optimization 14

15. Results
• The visualization could presented to
the user using Gantt charts or bar
chart
• The projects are allocated in weekly
bases.
• The developed algorithms has been
run exploiting real Fluidhouse data
with several solvers like JuMP’s
default opensource Cbc solver and
high-performance commercial
solvers Fico Xpress and Gurobi.
• The experimented commercial
solvers were found to be about ten
times faster
An Approach to Production Scheduling Optimization 15

16. Validation of The Pilot
By the end of the project, the enhancement of the performance is
expected to be as follows:
• Number of client inquiries will increase 20%;
• Customer satisfaction will increase by 20 points following the
customer satisfaction questionnaire;
• On-Time-Deliveries will increase over 5 %;
• OTD deviation will decrease by 2-5 days;
• Number of reclamations will decrease by 10-15%;
• The average time period between order confirmed and order
delivered will decrease 20 %;
• Electrical energy consumption in product test area will decrease by
15%;
• Electrical energy consumption in calibration system will decrease
by 15%;
• Time spent in rework/repair will decrease by 10-15%.
An Approach to Production Scheduling Optimization 16

17. Conclusion
• C2NET platform is capable of addressing the needs of SMEs
with respect to information exchange and visibility across a
supply network, coupled with automated and collaborative
production planning and supply management.
• Fluidhouse sees a great potential in the C2NET platform, as
it provides the opportunity to increase visualization and
collaboration possibilities with customers and suppliers.
An Approach to Production Scheduling Optimization 17

18. Future work
• Focus on the other two scenarios of the pilot, i.e Order
Reception and Delivery Planning, and Purchase Planning
scenario.
• Mobile notifications to customers about production state
changes.
• Exporting the optimized Production Plan back into Fluidhouse
enterprise systems.
• Exploiting C2NET Collaboration Tools for collaborative
decision making with customers and suppliers.
• Developing UIs to the end users on factory floor, including
visualizations.
An Approach to Production Scheduling Optimization 18

19. Acknowledgement
The research leading to these results has received funding from the European
Union’s Horizon 2020 research and innovation program under grant agreement
n° 636909, correspondent to the project shortly entitled C2NET, Cloud
Collaborative Manufacturing Networks.
An Approach to Production Scheduling Optimization 19

20. THANK YOU!
Any questions?
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An Approach to Production Scheduling Optimization 20