Industrial Equipment

Transforming Products and Connectivity for the Industrial Equipment Industry

Capital and Industrial equipment manufacturers know about pressure. Their products are mission-critical for the businesses that rely on them. Whether it’s Semiconductor Manufacturing Equipment, Critical Material Handling Infrastructure, or Discrete Production Systems, unplanned downtime is not an option. When this type of equipment fails, it means loss of productivity and revenue. In an industrial setting this can add up to significant loss of revenue in a matter of hours.

With stakes like these, why not make Capgemini Engineering IPD your development partner? We offer end-to-end engineering expertise, system architecture consultants and data scientists to develop and support complex control systems. In addition, we are highly-skilled at leveraging new technology, the IoT, predictive maintenance and data analytics.

Consulting and Development Services

Our Consultants bring decades of industrial experience to bear to help define the requirements and critical architecture for your product. Our team of 50,000+ development engineers will accelerate your time to market by providing high quality, system-focused and process driven development of your complex products.


We can add connectivity and integration into smart manufacturing environments, as well as reduce service, maintenance and warranty costs. We specialize in embedded controls, motion control, telematics and analytics.


Engineering Support Services


Our group provides cost-effective sustaining and maintenance services to support and preserve your existing hardware and software products. We have extensive experience providing value engineering and modernizing equipment and can create alternatives to address parts obsolescence while preserving product functionality.


Sectors Served: Semiconductor Manufacturing Equipment, Material Handling Equipment, Discrete Manufacturing Equipment


Industrial Equipment Case Studies:




Identified the most compelling IoT cases.


The Situation:


Manufacturer of hot beverage brewing systems was facing intense pressure to add features and functionality that leverage the IoT. They need help identifying the most compelling features and functionality to appeal to new and existing customers.




  • Identifying multiple connectivity, user interfaces, data transfer, capabilities, and scenarios to add to their product
  • Determining the most beneficial IoT capabilities to build into the product
  • Testing a wide variety of customer use cases



  • Designed and built a new test platform in 4 months
  • System included multiple connectivity options, user interface methods, and data storage options
  • Customized various use cases to set up specific trials for consumer testing

Proven Results:


  • Able to identify the most compelling IoT use cases with new test platform
  • Expanded use cases to gain detailed insights for specific product features
  • Gained an understanding of how to productize IoT features


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Predicted and prevented numerous egregious failures by implementing predictive models.


The Situation:


A global capital equipment supplier who was dealing with high warranty and service costs for thousands of units running in the field knew that predictive analytics could be a viable solution for driving costs down and assisting in preventing equipment failures in the field, but the current data handling solution was incapable of processing the massive amounts of collected data.




  • No predictive analytics being used on collected data
  • Data mining environments overwhelmed by large data volume and unable to interpret data
  • Current data handling solution cannot process massive amounts of data
  • Limited resources and lack of available in-house expertise



  • Reviewed and improved the data infrastructure
  • Implemented advanced data analytics, reporting, and integration
  • Created a full data preparation cycle which improved data quality
  • Put predictive business rules into effect and added predictive modeling to the infrastructure

Proven Results:


  • Effectively stabilized platform and overcame data quality issues
  • Provided model templates to feed into a Model Factory
  • Delivered models achieved necessary quality gates
  • Predicted and prevented numerous egregious failures by implementing predictive models
  • Significant, ongoing improvement to equipment reliability and performance in the field


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Created “the demonstrator” to test microchips faster, more efficiently and at less cost.


The Situation:


A leading manufacturer of measuring instruments used in the design, production and maintenance of electronic systems, wanted to leverage automatic test equipment and custom tools to provide faster insight during their microchip testing process.




  • Selection of the representative mathematical tests for defect discovery and diagnosis and identification of root causes
  • Selection and evaluation of adequate analytics tools
  • The database was the key interface for data tracking during the test process
  • The final database design would need to balance scalability, flexibility, versioning and accessibility



  • Detailed review of the successful manual experiments already conducted
  • Define and prioritize features to be included in the “demonstrator” (automated testing tool)
  • Design suitable data transformations and features
  • Find correlations, patterns and predictions to generate useful analytical input

Proven Results:


  • Faster time-to-market for new chip designs
  • Reduced repetition of steps between designers and characterization engineers by using the automatic, proactive testing
  • Creation of new, analytics-assisted test strategies
  • Lower overall cost of testing


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Download our Industrial Equipment Case Studies

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