Optimization Algorithms forFlexible Production Scheduling

Zdenek.Hanzalek@cvut.czthanks to : P. Sucha, I. Modos, Z.Baumelt

Czech Institute of Informatics, Robotics and CyberneticsFaculty of Electrical Engineering

Czech Technical University in Prague

Supply Chain Management and Scheduling

Sales Material Production Distribution

• Supply chain is driven by the customer demand• Production needs to be very flexible • Scheduling and rescheduling is needed to achieve efficiency

Application:Flexible planning and scheduling in 

printing company

Planning and Scheduling

Planning layer - typically in ERP• Works with cumulative capacities in

buckets of time (like day-week) • Loads operations into buckets • No account of sequencing,

precedences, set-up time

Scheduling layer• Exact start time of each operation• Completion time of job is known• Operations allocated to machines• Takes into account set-up times,

types of resources, transport times• Brings savings and order

Flexibility

Mike Tyson: „Everybody has a plan - until he gets hit.“

Manufacturing is hit very often:

• Machine breakdown

• Material unavailability

• Order with high priority

• Sick-leave of personnel

Solution

Integration withMES&Rescheduling

Resource productivity and efficiency

Information Systems

ERP• Orders

• Material

• Know-how

CPS• Events

Flexible Scheduling

AlgorithmsProcesses

• Optimization algorithm coupled with existing ERP

• Recalculation of the production plan every 30 minutes

• Objective is a maximal use of the most expensive machines

• Sales personnel adjust timing/price of orders up to the available capacities

• Uptime increase from 30% to 40% due to the reduction of changeover times

• Fully automated

Machine‐Uptime in Printing Company

Sales

• inserts jobs

Planner

• checks availability of

resources

• adapts global schedules

Users and their roles

Foreman

• sees a schedules/status

Worker

• sees a sequence of operations

Warehouseman

• bill of materials to be ready

Fabrio – internet service

Histogram of Up‐timeBefore and After

0102030405060708090

1000 20 40 60 80 100

120

140

160

180

200

220

240

260

280

300

320

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360

2014 avg 41,3%2012 avg 30,5%

• Today – increasing number of small orders • Replacement of sales personnel by Web2Print

Case Study:Robust Scheduling with Energy

Consumption Limits in Glass Hardening

Robust Scheduling withEnergy Consumption Limits

• Energy-aware scheduling – consumption limitsper 15 mins

• Uncertainty of execution – disruptions, materiál, …

• Robustness of theschedule is a necessity to avoid panalties

• Development of exact and heuristic alorithms

Case Study:Energy efficiency of Skoda Gear

Box Production Line

Production line for automatic gear box consists of:1. machine tools center2. hardening line3. assembly

Energy Efficiency of Hardening Line

• hardening is the most energy consuming stage

• CURRENT SITUATION: even if a hardening furnaces is not used it is not switched-off due to the luck of the schedule

• SOLUTION: The aim is to switch between operational and standby modes of hardening furnaces

• relation between production scheduling and cost of energy

Case Study:Robotic Welding Cells in

Car Manufacturing

Parameter and Code Generation in Digital Factory

• Generation of parameters and real robot programs 

• Cycle‐time and energy• Order of operations• Robot trajectories ‐movements, spot welding

• Shared zones ‐ robots must avoid collisions

Tecnomatix Process SimulateReal Experiments by Blumenbecker

Robot Energy Consumption

1. selection of stationary positions

2. power save modes

3. trajectory selection

4. speed of movement

5. order of operations

We consider the following categories of saving:

Tasks and Precedence Constraints● graph representing two robots

● schedule

Personnel scheduling

Department of Control Engineering

Set of employees with qualificationsSet of shiftsSet of constraintsMultiobjective criterion

Goal - to assign required shifts to employees with respect to given constraints

labour codecollective agreement

…all shifts assignment, coverageminimal time gaps between shifts,maximal length of blocks, balancing

…

Verification of real-time systems

• timed automata, temporallogics

• cooperative-preemptivescheduling

• case studies in automotive sector

• modelling of fault tolerant systems

• distributed applications based on CAN

Finishing timeP-high

CP-highin [1,2]

Finishing timeP-low

CP-lowin [1,2]

0 1 2 3 40

1

2

• Waszniowski, L. - Hanzálek, Z.: Formal Verification of Multitasking Applications Based on Timed Automata Model, Real-Time Systems, Volume 38, Number 1, January 2008

• Waszniowski, L. - Krákora, J. - Hanzálek, Z.: Case Study on Distributed and Fault Tolerant System Modelling Based on TimedAutomata. Journal of Systems and Software, 2009

Message Scheduling for Profinet IO IRT

Hanzálek, Burget, Šůcha, P.: IEEE Trans. on Industrial Informatics, 2010.

Tree topology• switch integrated in each node• data are forwarded according to

a static communication schedule

Formulated as PS|temp|Cmax

Parallel Optimization Algorithms

Graphics Processing Unit• Collaboration with

NVIDA (NDA, visits in Palo Alto)

• solve combinatorial problems on GPUs

Tabu Search algorithm• 10.5/42.7 times faster

than the optimized parallel/sequential algorithm for the Central Processing Unit (CPU)

Bukata, Šůcha, Hanzálek: Journal of Parallel and Distributed Computing 2015

Journal papers in 2016

1. Bukata, L. - Šůcha, P. - Hanzálek, Z. - Burget, P.: Energy Optimization of RoboticCells, IEEE Transactions on Industrial Informatics, 2016.

2. Módos, I. - Šůcha, P. - Václavík, R. - Smejkal, J. - Hanzálek, Z.: Adaptive online scheduling of tasks with anytime property on heterogeneous resources, Computers and Operations Research, December 2016, Volume 76, Pages 95–117, Elsevier.

3. Václavík, R. - Šůcha, P. - Hanzálek, Z.: Roster evaluation based on classifiers for thenurse rostering problem, Journal of Heuristics, October 2016, Volume 22, Issue 5, Springer.

4. Dvořák, J. - Hanzálek, Z.: Using Two Independent Channels with Gateway for FlexRayStatic Segment Scheduling, IEEE Transactions on Industrial Informatics, October 2016.

5. Hanzálek, Z. - Šůcha, P.: Time Symmetry of Resource Constrained Project Schedulingwith General Temporal Constraints, Annals of Operations Research, Springer.

6. Minaeva, A - Šůcha, P. - Akesson, B. - Hanzálek, Z.: Scalable and EfficientConfiguration of Time-Division, Journal of Systems and Software, March 2016, Volume113, Elsevier.

7. Hanzálek, Z. - Tunys T. - Šůcha, P.: An Analysis of the Non-preemptive Mixed-criticalityMatch-up Scheduling Problem, Journal of Scheduling, October 2016, Volume 19, Issue5, pp 601–607, Springer.

8. Bäumelt, Z. - Dvořák, J. - Šůcha, P. - Hanzálek, Z.: A Novel Approach for NurseRerostering based on a Parallel Algorithm, European Journal of Operational Research, June 2016, Volume 251, Issue 2, Elsevier.

Awards in 2016

Excellent Research Results in Technical Sciences • evaluation was based on impact of the paper measured in terms of

contracts and citations • our group got 2 results out of 42 awarded in Technical Sciences in the

Czech Republic

Hanzálek, Z. - Burget, P. - Šůcha, P.: Profinet IO IRT Message Scheduling with TemporalConstraints. IEEE Transactions on IndustrialInformatics, August 2010.

Hanzálek, Z. - Jurčík, P.: Energy efficientscheduling for IEEE 802.15.4/ZigBee. IEEE Transactions on Industrial Informatics. 2010.

Projects and Contracts in 2016

1. HERCULES - High-Performance Embedded Real-timeArchitectures for Low-Power Many-Core Systems, EuropeanCommission 688860. Horizon 2020.

2. FOREST - Flexible Scheduling and Optimization Algorithms for Distributed Real-time Embedded Systems - GACR.

3. SALTT - Scheduling Algorithms for Time-Triggered Systems, Office of Naval Research Global N62909-15-1-N094, US Navy.

4. CAK 3 - Centre for Applied Cybernetics - TACR.5. eRobot – Energy efficiency of robotic welding cells – Ministry of

Industry and Trade.