Predictive solutions for manufacturing

Networked systems that access algorithmic calculations process unrestricted amounts of data. They calculate all options and generate prognoses with which companies can predict operations. Predictive solutions are the way to plan the work of tomorrow.

Digitalisation is changing the face of industrial production. The digital innovations in recent years have given rise to networked systems that achieve highly efficient production and at the same time increase quality exponentially. Linked with big data analyses and artificial intelligence, these systems enable predictions about the condition of certain systems or installations and about customer behaviour. Thanks to predictive solutions, companies can quickly, precisely and reliably plan their resources, which establishes a true competitive advantage. In this context, the greatest challenge is extracting real and useful information from massive quantities of data. Only those who sort the data well, systematically prepare it, correctly analyse it and finally convert it into reliable predictive models succeed at this.

Jörg Lang
Divison Manager

ELCA Informatique SA develops tailored industry solutions for manufacturing and helps clients to boost productivity and efficiency. When developing these solutions, ELCA focuses on integrating the entire value chain – from initial contact with the customer to the supply chain and customer service – into a single, continuous process. ELCA is the leading provider of customer relationship management (CRM) solutions for sales and marketing, and solutions for after-sales service. The company also has the expertise and experience to support clients with every aspect of data analysis, data management strategies, CRM, cloud services, security solutions, processes and collaboration.

Predictive solutions

Predictive solutions use integrated data processing to calculate the requirements of units or the development of elements within the system to provide information that allows sales and production to make pre-emptive decisions and eliminate the need for after-sales service before it arises. This reduces costs and enables companies to use the data to optimise and even automate the routes and work schedules of service technicians, which has a positive impact on the environment as well as the bottom line. Users employing predictive solutions benefit from complete transparency with regard to the various platforms, allowing them to improve specific areas of the customer experience.

Predictive maintenance

SBB, the Swiss national railway company, runs a busy 6,000-kilometre rail network that costs CHF 800 million a year to maintain. The predictive solution ELCA designed for SBB optimised the maintenance of the network with digital technologies and modern data analyses that are capable of predicting where maintenance and repairs will be required. This minimises the costs of repairing faults in the network, improves the safety of the infrastructure and minimises the risk of accidents. ELCA collaborated with the infrastructure experts at SBB to create the data lake and analysis models that were required to develop this solution.

Contact: Jörg Lang

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