Founded in 1956, Carlson Products originally manufactured wall ties, window and door frames, aluminum stockroom doors, grain traps and tool boxes. Now Carlson is a major supplier of formed and fabricated component parts as well as finished aluminum products for commercial bakeware, industrial, doors, and restaurant leaders throughout the United States and abroad. Products are stamped from aluminum, stainless steel, galvanized steel, and other metals. One of Carlson’s unique specialties is design assistance for component parts or original product concepts and designs, including production of prototypes.
Attempts to manually track data were previously unsuccessful, and lead to what the company called "Junk data". On the heels of a new ERP integration, Carlson new it was critical to get good data to empower its success. To get data into their ERP, they relied on operators to accurately define and manually input this information into their database, which was time consuming and lead to inaccuracy. With a focus on historical labor data, it was essential to know whether or not jobs were on target. Tracking down supervisors and operators to understand why jobs were late was extremely time consuming, and employees had difficulty remembering why problems had occurred. There was no ability to identify systematic issues vs. singular issues, and the lack of historical data made it difficult for them to calculate true machine utilization as well as their potential capacity.
MachineMetrics was chosen because of its capability to connect to to all of Carlson's various pieces of equipment on the shop floor and collect data automatically. Leveraging the scalability, flexibility, reliability, security, and cost effectiveness of AWS, MachineMetrics allowed for data aggregation across all of Carlson's shop-wide systems, the ability to build custom applications, dashboards, and analytics that provided the right data to the right person at the right time.
Tablets were mounted to each machine to display job performance and provide operators with an interface allowing them to categorize downtime, setups, part rejections, and tool changes. Real time dashboards were installed on large screen monitors across the facility to provide real-time visibility into the performance of jobs relative to the company's production goals. Instant text notifications were set up so Production Managers could identify underperforming machines immediately and quickly address issues in real time.
