Calgary-based Nova Chemicals was struggling to process more than 20,000 maintenance work orders per year at each of its 11 chemicals and plastics resins manufacturing facilities. To improve its maintenance scheduling, the company introduced advanced analytics and cloud computing in collaboration with Enterprise Asset Management software (EAM). Today, the EAM software provides a complete and consolidated view of scheduled maintenance at Nova Chemicals. It facilitates maintenance scheduling, work execution, and material availability processes.

Logistics company Knapp AG developed a paperless picking technology that uses augmented reality to optimize the picking process in a warehouse. This wearable technology resembles eyeglasses and is worn as a headset by the employee.

An automotive OEM was experiencing increasing warranty expenses and recall execution costs driven by a reactive approach to issue identification, the long turnaround time between issue identification and resolution, and the inability to track the effectiveness of production and field fix issues. Real-time data was captured by sensors on the manufacturing line and aggregated with quality, warranty, and safety data to populate a cloud-based data lake. Advanced analytical techniques, including text clustering, probability analytics, concept extraction, and event history were utilized to identify potential issues. Digital user interfaces were leveraged to drive user adoption and enhance employee ability to translate insights into action. An end-to-end set of dashboards was utilized to create visibility into priority issues, enabling the execution of field fix implementations sooner.

A major coffee manufacturer needed to reduce the percent of machines that were offline for cleaning. To keep the production rates steady, the manufacturer needed to purchase 100 extra machines to compensate for the offline equipment or find a better solution. The coffee manufacturer chose to implement an IoT solution to enable the coffee-production equipment to generate a real-time information stream regarding its operational state. This enabled the company to more effectively predict downtime and significantly decrease the extent of surplus equipment needed on the production line.

Lido Stone Works manufacturer of high-end architectural stone products. Seeking to realize a more-automated production environment, Lido Stone Works leveraged IoT to craft an intelligent manufacturing system that directly links Lido and their clients’ architects into a seamless, IoT-enabled cloud platform. The platform generates a real-time stream of information, and both the client and technicians can monitor a job’s progress in real-time, detecting, and fixing, problems as they unfold.

KUKA Industrial robotics manufacturer. KUKA seized the opportunity to integrate IoT systems when the company built a new facility in Toledo, Ohio for manufacturing Jeep Wrangler bodies. KUKA connected over 60,000 devices, including 259 assembly-line robots, into a central data management system. By linking the devices, line-of-business applications, and back end systems together, KUKA has achieved an automated manufacturing process capable of producing one of eight different Jeep Wrangler auto bodies every 77 seconds off the same production line without interrupting production flow.

HIROTEC America Automation manufacturing equipment and parts supplier with 26 facilities in 9 countries that designs and builds approximately 7 million doors and 1.5 million exhaust systems annually. Volumes of data were manually separated and stored across multiple sources. To improve quality, reduce downtime, and optimize production schedules, HIROTEC needed to implement a modern, automated solution that could gather maintenance and operational information into one source and offer actionable recommendations. HIROTEC turned to IoT and connectivity platforms to enable company-wide device-to-cloud connectivity through one overarching toolset. A manufacturing suite and IoT Gateway advanced plug-in was also part of the solution.

Kaeser Kompressoren German-based manufacturer of compressed air systems and services.  To avoid unplanned outages and system downtime, Kaeser began equipping its compressed air equipment with IoT sensors that capture key environmental and performance data such as temperature, humidity, and vibration. With equipment continuously transmitting operational status in real-time, Kaeser conducts predictive analytics to determine whether parts might be prone to failure and to identify and replace faulty parts during regularly scheduled maintenance instead of after an outage has occurred. Kaeser upgraded to a relational database management system to orchestrate new business processes across the organization, improve supply chain management, and harness the power of big data analytics.