A large manufacturer examined several Asset Performance Monitoring (APM) solutions with the goal of improving productivity and resolving bottlenecks in operations. The company has around 100 critical production assets, spread across 4 organizational units, manufactured by multiple vendors and varying in age. They employed a new APM technology that helps manufacturers digitalize their machines to become an industry 4.0 “factory of the future”. The solution generates visibility and actionable insights within hours, using a range of highly accurate, non-invasive sensors and a cloud-based APM platform. The edge devices and sensors were installed in stages on more than 100 assets. Machine availability, real-time status, and historic reports are now being shared on the shop floor. The newfound transparency creates a company-wide commitment to goals and builds motivation to improve. Prior to the introduction of the APM solution, the assets were monitored by traditional tower lights, as well as handwritten logs and departmental whiteboards. In order to improve, the company needed a unified and consistent method of data collection and analysis. The company assessed this new APM solution versus a common APM solution that uses 24V controls and tower lights. After an 8-week trial period, this AI-powered solution was selected, and the company became a design partner. Using the new solution, the company now has automated and reliable visibility into the production floor, providing an accurate and real-time status of machine availability, and has enabled improved processes by facilitating data-driven decision making. The new APM solution improved machine productivity in some of the production floors by more than 30% within months. Comprehensive reports generated from the data is shared with shop floor staff, creating new transparency, trust and continuous operational improvement.

This solution involves converting the readout of a traditional analog gauge information into digital data using a sophisticated vision system. The system is deployed in a brewery. They had many old fully functional pieces of equipment such as boilers, stills, etc. These were all controlled and monitored by humans using traditional analog instruments. In the solution an intelligent camera system converted the analog information into digital information that was fed into a computer system for downstream analysis. The major advantages were reducing the amount of time required to measure, ensuring that measurements were taken at a precise schedule with fewer errors, and the ability to increase the frequency of measurements.

The end user can train the AI to identify objects by simply highlighting pixels in an uploaded image or images and then naming the image. The AI system will then use any end user camera input to "look for" the image desired. The system works by storing like images in a large neural network in the cloud. When it finds a match the system can then run a user defined script, like sending a message to a cell phone, or triggering the next work process. Company is based in metro Detroit.

A coffee retailer wanted to update a feature in its mobile application to give customer's a much better ordering experience. With the new voice ordering feature, customers could designate their regular Starbucks order in advance, then place the order from one their ten most visited shops, using their voice with a voice ordering-enabled device. This helped the retailer grow more revenue.

A software developer used artificial intelligence (AI) to provide a convenient self-service portal for managing payments and tariffs. The developer used jQuery and mediaQuery to distribute code among several servers. Frequently used data were stored in Memcache. With this solution, a nice and clean self-service portal with rich payment functionality was provided for users.