SAP Leonardo IoT Edge SAP Intelligent RPA Plant

SAP® Innovation Awards 2020 Entry Pitch Deck

SAP Intelligent RPASAP Leonardo IoT Edge

Plant Connectivity (PCO)

SAP Data Intelligence

(Data Hub)SAP Analytics CLoud

Martur Fompak International

PIONEER - Increase the Usage of Renewable Energy and Reduce the Carbon Footprint

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Company Information

Headquarters

Industry

Web site

Istanbul, Turkey

Automotive Seating

www.martur.com

Founded in 1985 to produce molded foam, Martur is now one of the world’s leading suppliers in automotiveseat production. Having 12 production plants in Turkey, Romania, Russia, Algeria, Morocco, Poland,Ukraine,Italy with more than 6000 employees, Martur continues to make new investments . The companydesigns and manufactures seats for passenger cars and light commercial vehicles, designs andmanufactures integrated fabric and seat structures for the automotive industry. The company provides itsservices to leading domestic and international OEMs.

Martur is a member of a group of companies that supply high quality products to the automative industry.With R&D and design offices in multiple locations in Europe, Martur continues to set the standards for theindustry.

Integrity and focus on people assure that Martur’s excellence spans across every level of our business. Ourlong history of positive and effective employee practices provide us with a set of beliefs, approaches andtools that we implement even in the finest details of our business. In light of with our core values, we harbor adeep commitment to our employees. Developing and motivating our people as innovators and leaders formsa cornerstone in our management approach, which we believe it is the main driver our success.

Martur is commited to the SDG’s by UNGC; especially for climate action.


Challenge

Solution

Outcome

Global sustainability goals are

included into MFI objectives by

the sign of the letter of

commitment of UNGC in 2012. We,

MFI, are always willing to be a

pioneer to implement

innovative activities. In these

days, all of us feel the reverse

effect of global warming in daily

life. We take the responsibility to

reduce our contribution in climate

change by following strictly SDGs,

especially climate action,

affordable and clean energy. We

gain the most important benefit by

implementing AI into energy

management for eliminating

energy consumption during non-

production time and selecting

renewable energy source to

consume in order to reduce our

carbon foot print.

Özlem Altınışık,

Director Information Technology,



We stored the data received from IoT devices on SAP HANA were stored and data are processed instantly with SAP Data Intelligence (AI) to increase

the energy efficiency of the machines. Thanks to ML that the future energy consumption were estimated efficiently by evaluating the production

planning data obtained from ERP / APO and energy consumption data obtained from MII. Besides, we anticipated the rate of renewable energy by

analyzing the data of energy sources firms and this will be used in the future to plan production to use more renewable energy. We reported all

processes were reported instantly with SAP Analytics Cloud.

As a result of this project, the energy consumption in non production time were reduce significantly and the renewable energy consumption was

increased in production time and so, carbon footprint was reduced.

6%

To collecting data from 12 plants in 8 different countries and analyze them by MII and AI to find out the best solution to reduce the

energy consumption, green house gase emission and to increase the usage of renewable energy sources.

Rate of usage

Renewable

Energy

Green House

Emission

Reduce

PIONEER

Rate of reduced

useless electricity

consumption by

MII and AI

20% 4,5%


Participating Partner Information

"The PIONEER project which aims to increase the usage of renewable energy and

reduce the carbon footprint is an amazing example of SAP’s purpose of helping the

world run better and improve people’s lives. That’s been our purpose from day one.

We’re glad to help MFI run their best and achieve their goals by delivering the right

technology."

Ugur Candan, MD, SAP Turkey

SAP TURKEY

Technical Support for Data Intelligence / Data Hub


Business Challenges and Objectives

We, MFI, aim to be the leading seat manufacturer in the World with the our company culture which puts the human being to the first

priority. For that reason by increasing the use of renewable energy and reducing our carbon footprint we contribute to reduce the

reverse effects of global warming.

P Prediction , I Intelligence, O Optimization, N New & Innovative, E Environment, E Energy, R Renewable

In line with this priority; the instant data should be analyzed to eliminate the energy losses in our machines and to increase the use of

renewable energy sources.

▪ To eliminate energy losses in our machines, instant data should be analyzed to stop the machines during non-production time.

▪ To increase the usage rate renewable energy usage rate in production, we should forecast the seasonal trends and the time

intervals for which we can benefit from maximum renewable energy in the future.

Project Objectives

▪ To eliminate the useless energy consumption by switching off the equipment with integrated sensors

during non production time.

▪ Forecast our future consumption by analyzing our energy consumption behaviours.

▪ To analyze the renewable energy supplies and plan production according to renewable energy sources

▪ To reduce carbon footprint.

Project is called as «PIONEER» to match with our challenging objectives.


Project or Use Case Details

We, MFI, aim to be the leading seat manufacturer in the world and we prioritize to increase the energy efficiency and to reduce the carbon

footprint. With the [Pioneer] project, we aimed to increase the consumption of renewable energy sources and to minimize energy losses with

artificial intelligence solutions.

In line with our company objectives, we eliminated energy losses on machines by controlling the data received through IoT with artificial

intelligence on SAP Data Intelligence / Data Hub. By obtaining data from SAP MII, we analyzed the amount of energy consumption per product

with HANA PAL library and determined product / workcenter based consumption trends and predicted future consumption through production

plans obtained from SAP APO/PPDS module.

We have estimated the ratio of renewable energy sources ratio and the future rates of these sources by obtaining the amount of electricity

generated by the government through DataHub service. By including solar energy generation amount in MFI, we have recorded the ratio of actual

amount of renewable energy consumption.

By combining these data, we have estimated the renewable energy ratios of product / workcenter based consumption, as well as the renewable

energy to be consumed in the future.

We kept all of the data we used on the SAP Hana database and reported on the SAP Analytic Cloud to provide instant access to the results.

Next Stage:

▪ Implementation of the project in all locations

▪ Ensuring that production shifts are planned to use more renewable energy

▪ Detection of inefficiencies or abnormalities occurring during production and create warning



BW/BO

2014 2018 2019

USELESS CONSUMPTION

LOSSES

8%

OVER CONSUMPTION

LOSSES

3%

NON-OPTIMIZATION LOSSES

4%

170 Analizers

USELESS CONSUMPTION

LOSSES / WORKCENTER

2%

SAP

Analytics

CLoud

NON-OPTIMIZATION LOSSES

2%

OVER CONSUMPTION

LOSSES

1%

500+ Analizers

SAP IoT Edge

Plant Connectivity

(PCO)

SAP Data

Intelligence

(Data Hub)

2015 2016 2017



GREENHOUSE GAS EMISSION- TON CO2* 3558* 2018 Sustainability Report Emission Value

SAP ANALYTICS CLOUD POTANCIAL

GREEN HOUSE EMISSION SAVING

POTANCIAL SAVING 4,5% YEAR


Business or Social IT Human Empowerment

Benefits and Outcomes

Elimination of energy

consumption abnormalities

Forecasting future energy

consumption

Planning of production in order

to get maximum benefit from

renewable energy sources

Social:

Reduction on greenhouse gas

emissions and carbon footprint.

Contribution to SDG’s for the

future generations.

Reduction on global warming

effect

Encourage the energy supplier

to generate renewable energy

sources

Increase awareness of

employees on energy

consumption and encourage

them for good environmental

implementations.

Protect biodiversity and keep

habitats by reducing the effect of

global warming

Communication among systems

becomes easier and

standardized by using SAP

DataHub

Cloud architecture provides

uninterrupted access to reports

at desired details


Architecture


Architecture


Architecture


Architecture


SAP technologies used:

Date Number of users

Deployment status

Deployment

If you have used one of the services or support offerings from SAP Digital Business Services during the implementation or

deployment phase, please select with one or more of the following offerings:

SAP MaxAttention™

SAP Value Assurance

SAP ActiveAttention™

SAP Model Company

SAP Advanced Deployment

Others:

X

SAP Innovation Services SAP Innovative Business Solutions

January 2019 90

Live

SAP product

Deployment status

(live or proof of concept [POC]) Contribution to project

1 SAP Data Intelligence Live Data Orchestration pipeline and machine learning and prediction

2 SAP HANA Platform Live In memory data store and processing. PAL Machine Learning.

3 SAP Analytics Cloud Live Reporting

4SAP MII /SAP Plant Connectivity

(SAP PCo)Live

Integration with shop floor, measuring and monitoring of all energy

consumption / Exchange of bidirectional data with equipment

5SAP Intelligence Robotic Process

AutomationPOC Connection with governments official energy statistic.


The following advanced technologies were part of the project.

Advanced Technologies

Technology or use case Yes or No Contribution to project

1 3D printing

2 Blockchain

3 Internet of Things (IoT) YesWorkcenter and product based actual consumption amount are

calculated by processing the data instantly from the machines.

4 Machine learning or AI Yes

To estimate energy consumption and the ratio of renewable

energy by using Machine Learning technique. Abnormalities are

also detected in machine operations.

5 Conversational AI

6 Robotic process automation YesTransfer of actual energy consumption data published by official

institutions to S4HANA database.

7 Data anonymization

8 Augmented analytics


Additional Information

Pioneer Video Link;

https://vimeo.com/382645877

https://vimeo.com/382645877

Documents

SAP Leonardo IoT Edge SAP Intelligent RPA Plant