International deployment of CMMS: Adient’s case study

The global leader in automotive seating is pursuing Industry 4.0 by sharpening its focus on innovative technologies to implement its predictive maintenance.

Adient ($17 billion in turnover, 85,000 pers.) is the global leader in automotive seating and has cornered 33% of the market. With over 25 million seat systems installed and 238 manufacturing plants in 34 countries, the company supports all major automakers in differentiating their vehicles through high-performance products. It recently expanded its offer by entering into a partnership with the Chinese equipment manufacturer Yanfeng, which provides complementary components such as dashboards, roof panel trim, armrests, etc. As part of the 2018 International Maintenance Forum organised by AFIM, Martin Heckmann, Director of IT Operations Fabrics, Foam & Trim, Adient Seating S.A.S., shared his feedback on the international deployment of the DIMO Maint CMMS solution.

 

Need for a standard system for maintenance management

Flashback to 2014: The Johnson Controls group – which operated in the automotive seat and interior business at the time – did not have a common maintenance management strategy for its manufacturing plants. Its diverse locations (England, Malaysia, Thailand, etc.) needed a unified system, but there was no standard solution. Some plants required fast implementation, which made deploying a large system problematic. How do you modify a consistent approach knowing that the solution may need to be changed afterwards?

 

Specific selection criteria that cover all maintenance needs

Strict selection criteria for a solution were issued according to overall needs:

• Maintenance functions and options
• Spare part functions and options
• Integration complexity
• Support resources
• Deployment need
• Cloud and on-site models
• Cost model

Martin Heckmann explains: “4 solutions were evaluated. Adient had already tested each one and most of the solutions covered its functional needs. DIMO Maint was used at the group’s Strasbourg plant, and was ultimately selected thanks to its deployment speed and cost structure.” A functional pilot was carried out in England, before deployment to seven of the group’s “Fabrics” plants.

 

A proven and rigorous deployment methodology

Three steps were implemented:

An MSA (Master Service Agreement) was put in place to ensure everyone’s roles and responsibilities. The main components included contract duration and termination, technician conditions, confidentiality, intellectual property, and warranty terms.

• DIMO Maint provided the concept of “General Design by Product Group” which proved essential to the project’s success by speeding up deployment. It therefore made it possible to pinpoint a global standardisation method by working cross-functionally with the professions and IT staff. It took into account all the software’s features/settings/tables and created databases based on activity.

• Finally, a SOW (Statement of Work) defined a deployment contract.
A plant was deployed in about a week.

 

Full compliance with the maintenance plan

Standardisation of the basic data made it possible to generate indicators, observe maintenance savings garnered through continuous improvement, and compare costs per manufacturing plant, the respective downtimes, etc.
The plants fully complied with the preventive maintenance plan.

 

Integrating Industry 4.0 components

 

Adient hopes to double the number of plants using the system within 12 months.
This project is part of an Industry 4.0 vision that integrates an important analytical layer with two main objectives: identifying production efficiency and monitoring maintenance budgets.

The mobility of the DIMO Maint solution – which is also part of the cloud, ensuring rapid deployment – offers great flexibility of use: the technicians can create visit reports usable by the analytics, the speed of operation being crucial for the plants to function properly.

The various business building blocks that make up Adient’s industrial information system (ERP-MES) are communicating. The main information sent via the connectors includes purchase requisitions, stock movements, planned outages, equipment alarms and breakdown forecasts.

The goal? Develop a real predictive/anticipated maintenance approach for:

Reducing repair time
• Reducing downtime
• Extending the life cycle of expensive equipment

DIMO Maint is keeping with this “4th industrial revolution” by integrating the new possibilities offered by innovative technologies such as IoT, Predictive Maintenance, BIM, Big Data and Artificial Intelligence. DIMO Maint surrounds itself with specialised partners in order to study:

• CMMS data or machine data available on site
• the possibility of setting up or using new data sources (machine data, IoT, algorithms, AI, etc.).

In summary: digitising maintenance is a key focus of the industry of the future for Adient. DIMO Maint proposes analysing and implementing innovative solutions to optimise predictive maintenance, thus contributing to a better understanding of the overall cost of the plant.

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