The needs:

To develop a system for managing data covering:

• The real-time recovery and the improvement of the quality of the test results
• The standardization of the data formats, the storage and the archiving of the data
• The distribution of the data on request (based on events) in different formats

To facilitate the integration of external solutions in the production environment

• To drive software on request from the production management system
• To get back events and alarms to fill the follow-up database

Methodology:

Support of business owners

• Identification and formalization of requirements
• Writing user requirements

Pre-project study

• Identification and modeling of applications and data
• Identification and evaluation of alternative solutions; feasibility study
• Definition of the overall system architecture
• Estimates of costs, effort and time

Project management

• Technical design and detailed specifications
• Definition of validation tests
• Management of the development team

Results:

Modular data management system including:

• A database for the equipments, recipes and results
• Modules for the data loading, translation, control and export
• Graphical user interface

Integration module for the statistical software automation based on standard protocols:

• Bi-directional interface with the production management system
• Analysis software automation and feeding repository with the results

The needs:

To improve the systems monitoring and to anticipate incidents

• To identify the risks, their impacts and the indicators allowing to anticipate the malfunctions
• To define processes, procedures and organizations in case shift in key performance indicators
• To define processes, procedures and organizations in case of malfunction detection
• To build the dashboard with metrics on the levels of services

Methodology:

Audit of the systems
Business owners have been fully involved in modeling and risks analysis. So they fully supported choices and decisions later on in the project.

• Identification and modeling of the critical business processes,activities and information flows
• Identification and modeling of the applications, data and infrastructure
• Identification of the key indicators of the business performance to monitor
• Risks analysis (FMEA): Identification of the IT systems linked to critical business activities

Implementation of the supervision

• Choice of the tool to support supervision needs: Open source Zabbix integrated with HP Open View
• Implementation of the monitoring procedures with Zabbix agents or dedicated scripts
• For each alarm, documentation and associated procedures have been delivered
• Elaboration of the dashboards providing metrics and trend of the key performance indicator
• Definition of the service level agreement (SLA) and associated controls and reports for each business critical activity

Results:

• The comprehensive analysis of systems and their criticality to a supervised process and systems reviews
• Indicators' value and alarms are now generated by production system and treated accordingly to the defined and deployed recovery procedures
• Supervision needs and maintenance are included in the software delivery life cycle to guarantee maintenance of procedures and metrics
• Levels of dysfunction down 20% over 6 months
• A reduction of 50% of downtime for system crash thanks to reduction of the recovering time

Based on an obsolete technology and with limited functionalities, it was quite impossible to do changes in the Manufacturing Execution System. Furthermore, the replacement of this package by a new one was not feasible due to the complexity of such a project and its very high cost.

The needs:

Adapting the production control system to new business needs

• To facilitate the exchange of information between the MES and its environment
• To implement new functionalities and to integrate them with current systems and processes
• Mitigate as much as possible risks and impacts on production
• To deliver such solution within short timing

Methodology:

Modeling of current systems and new needs

• Identification of the critical business processes, activities, information flows and key performance indicators
• Identification of the existing applications, data and infrastructures
• Modeling of the global architecture (current and future ones)
• Evaluation of costs, workload and schedule

Project management

• Technical design and detailed specifications
• Definition of the tests and acceptance criteria with stress tests, errors handling and monitoring
• Management of the development team and implementation of the core components
• Overall technical validation before delivery

Results:

The delivery package consists of:

• A set of services, in high availability mode, providing robust and standard access to the data and functionalities of the MES
• New external modules integrated with the MES and supporting new needs
• Detailed migration and installation plans for each site and instance

Without having changed the current production systems, this architecture provides a solution to the users needs and allowed of:

• Minimizing the risks linked to a complete change of the production system
• Minimizing the costs of the implementation and deployment of this project
• Preparing the future evolutions of the system by delivering a robust and reusable layer of services on top of MES system
• All these, performed in timeliness of delivery

The needs:

To improve the data management :

• To have a database for critical data
• To improve the data quality level
• To put in place and track indicators measuring data quality
• To reduce data replication

Put in place a portal for data analysis :

• Collaborative and knowledge sharing environment
• Rationalization of data analysis systems

Methodology:

Support of business owners

• Identification and formalization of requirements in terms of analysis
• Identification of analysis methods and best practices
• Writing user requirements

Pre-project

• Identification of the existing applications, data and infrastructures
• Identification of the alternatives solutions and feasibility study
• Commercial package study and comparison
• Specification of the global architecture : Integration, technical choices...
• Evaluation of costs, workload and schedule

Project management

• Technical design and detailed specifications
• Functional and technical validations
• Management of development team

Results:

A data referential to an improvement in the quality and availability of data :

• An ETL open source solution to support in an efficient and flexible way the data transformations, quality control and flows
• Data referential with a layer of services to access them
• Dashboard with indicators for monitoring the quality and availability of the data, and the transformation processes

An integrated and collaborative environment for data analysis and knowledge sharing between all the engineers :

• Environment to share and to capitalize best practices of analysis at the company level
• Scalable system based on workflows for the implementation of the analysis processes
• Automated periodical analysis (reports, process control)
• Complete environment for the analysis of the causes of failure (follow-up, crisis period)