Arundo Analytics Announces Successful Deployment at Global Industrial Thread Manufacturer Coats

  • Deployment creates an unprecedented level of streaming, cloud-based global insights into machine utilization and overall equipment effectiveness
  • Arundo software identifies opportunities for Coats to improve operational performance
  • Arundo deployment is part of Coats global ‘Factory of the Future’ initiative, which aims to connect and improve operations internally and across the value chain

LONDON--()--Arundo Analytics, a software company enabling advanced analytics in heavy industry, today announced the successful deployment of Arundo software to improve manufacturing operations at Coats, the world’s leading industrial thread manufacturer.

“Coats has been a pioneer in industrial thread manufacturing for over 250 years,” said Edoardo Jacucci, Arundo General Manager EMEA. “We are excited to work with them as they continue to lead their industry by embracing IoT implementations for advanced analytics.”

The initial deployment of Arundo’s software collects over 800 machine signals at 1hZ intervals at the Coats manufacturing site in Shenzhen, China, in conjunction with operator, job, shift and site data. This access will create an unprecedented level of streaming, cloud-based global insights into machine utilization and overall equipment effectiveness. Based on the detailed granularity of these insights, concrete improvement actions can be rolled out across the business.

Coats has kicked off an ambitious global ‘Factory of the Future’ initiative, with the aim to connect and improve operations internally and across the value chain through machine learning and streaming data analytics. With 19,000 employees in over 50 countries, Coats operates a global supply chain and production operation across six continents.

“Our goal is to lead our industry by adopting and embracing the new technologies that may fundamentally change the way we do business,” said Hizmy Hassen, Chief Digital and Technology Officer, Coats. “Arundo provides deep data science, software and industrial domain expertise that can identify opportunities for us to improve operational performance.”

About Coats

Coats is the world’s leading industrial thread manufacturer and a major player in the Americas textile crafts market. At home in more than 50 countries, Coats employs 19,000 people across six continents. Revenues in 2017 were US $1.5 billion. Coats’ pioneering history and innovative culture ensure the company leads the way around the world: providing complementary and value-added products and services to the apparel and footwear industries; applying innovative techniques to develop high technology performance materials threads and yarns in areas such as automotive, composites and fibre optics; and extending the crafts offer into new markets and online.

About Arundo Analytics

With offices in Oslo, Houston and Silicon Valley, Arundo Analytics provides cloud-based and edge-enabled software for the deployment and management of enterprise-scale industrial data science solutions. Arundo's software allows industrial companies and other organizations to increase revenue, reduce costs and mitigate risks through machine learning and other analytical solutions that connect industrial data to advanced models and connect model insights to business decisions. In 2016, Arundo graduated from Stanford University’s StartX accelerator program, and subsequently received investment from the Stanford-StartX Fund. In 2017, Arundo was named to the MIT STEX25 by the Massachusetts Institute of Technology Startup Exchange (MIT STEX). MIT STEX25 recognizes select companies from a pool of more than 1,600 MIT-connected startups as being particularly well-suited for industry collaboration based on technical and commercial success. For more information, please visit www.arundo.com, or follow Arundo Analytics on Twitter @arundoanalytics.

Contacts

Treble
Ethan Parker, 512-960-8222
arundoanalytics@treblepr.com

Contacts

Treble
Ethan Parker, 512-960-8222
arundoanalytics@treblepr.com