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ARTISAN
Energy-aware enterprise systems for low-carbon intelligent
operations
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ARTISAN
• FP7 Research and Development Project funded by the European Commission, coordinated by ENEA.
• It involves 9 partners in 5 countries oni
• Purpose: Use of ICT in order to support the reduction of energy consumption and CO2 emissions in the Textile Manufacturing
• Beginning November 1, 2012, ending April 30, 2014
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How much energy the textile industry consumes?
• Electricity for spinning: from 3.6 to 5 MWh / t,
Energy (electricity and heat) for dyeing and yarning 8.41 MWh / t (*)
• Energy (electricity and heat) for weaving 2.80 MWh / t,
for dyeing fabric: 5.54 MWh / t,
for finishing 5.68 MWh / t (*)• Energy expenditure for a small business of weaving (1.32
million), amounting to € 513,045 for electricity and € 606,382 for gas (**)
(*) Data from EMS-Textile project (**) Data Processing provided by SMI
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The ARTISAN Approach
• ARTISAN aims to work primarily on daily operations of the company:
– Giving awareness of the actual energy consumption of machinery and disaggregated information about energy consumption on process step, process and / or product level
– Allowing the prediction of future energy consumption
– Optimizing production scheduling in order to minimize energy waste (for example, minimizing the time when the machines are turned on but idle)
• ARTISAN identifies and proposes a prototype of IT services that supports energy efficiency (divided into 5 levels) and a tool for energy performance self-assessment (ENCORE)
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Information Flows to be Integrated
Operational flow
Production process flow
Energy consumption flow
Energy and carbon footprint flow
ERP systems
WMS systems
MES systems
EMS systems
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ENERGY MONITORING AT PROCESS LEVEL
ENERGY AND CARBON EMISSIONS TRADING
ENERGY AND CARBON ESTIMATING AND PLANNING
ENERGY MONITORING ACROSS PROCESSES
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ENERGY –AWARE OPTIMIZATION OF PRODUCTION SCHEDULING
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Il prototipo di ARTISAN
• La struttura dei servizi
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Energy monitoring at process level (Service I)
• Collection and storage of energy consumption data through sensors, alarm management, calculation of consumption per process step and per order
For example, the production manager might realize that there is different consumption in different time intervals or in two similar machines
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Energy monitoring across processes (Service II)
• Modeling of energy consumption at the enterprise level, aggregate direct and indirect consumption to article level
This service provides an indication of the energy consumption at article level and allows a comparison with the benchmark values
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Energy and carbon estimating and planning (Service III)
• Estimate future energy consumption per process step and per produced order
Example of forecasted energy consumption on a weekly basis
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Energy-aware optimization of production scheduling (Service IV)
• The idea is to use the energy consumed as a parameter for production scheduling
• The result of the service is an optimized production scheduling in terms of energy consumption that will be sent to the MES
Optimization scenarios:a) Minimizing the makespan, thus implicitly minimizing the indirect energy consumption associated with the production support systems and facility, e.g., lighting, air-conditioning, b) minimizing the total idle time for selected machines or process steps, c) hierarchical optimization for both cases
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Gaant scheduling diagram
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Trading of energy and carbon permits (Service V)
• A service for purchasing and selling energy and carbon permits
• Unique platform for both types of products
• A service that could be used in smart grids
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EnCoRe
• Encore (Energy Consumption Reduction Tool) allows you to self-analyze the energy performance of the company and to compare it with benchmark values and suggests improvement best practices.
• It could be the step preceding the implementation of the ARTISAN system
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First Results
• Through analysis of real-time energy consumption data in machinery, captured by sensor network, Marc Cain (project partners) has identified new operating rules for electric machines with an average saving of 10% in fuel consumption.
• Through optimization, Marc Cain has identified possible reduction of machines stand-by time with potential electricity savings up to 20%.
• Through optimization, Fratelli Piacenza (project partners) has identified a promising area of heat consumption optimization by intervening on the production schedule of the finishing department in order to reduce the stand-by time.
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Thank you for your attention
ARTISAN site: www.artisan-project.eu
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