The Internet of Things (IoT) becomes reality for one of the top 500 fastest growing manufacturing companies in the US.
Although there's already much to read about the Internet of Things (IoT) for manufacturing in practice realization of such projects is extremely difficult business. Mainly because there's neither a common standard for communication between machines and business information systems nor a standardized method to pull out business relevant information from these devices.
However, by understanding and following some fundamental principles the customer was able to link together manufacturing processes with enterprise processes and master data in a simple and reliable way. This paper describes those principles, linking them together in a coherent journey covering the goals, the terms, the tools, and the decisions that were needed to successfully integrate the shop floor with the rest of the enterprise.
QUICK FACTS
Company
Location: Naples, Florida
Industry: Life sciences
Products and services: Medical devices
Revenue: US$ 1.5 billion
Employees: 3,000
Plants covered by the solution: 2
Manufacturing devices in total: 367
Production machines: 240
CNC controlled Machines: 100
PLC controlled machines: 140
Implementation partner: inventcom
Benefits
Minimized machine integration costs by only using software based solutions
Streamlined work order performance tracking across multiple plants
Enhanced visibility, integration, and efficiency by eliminating paper-based, manual business processes
Reduced time needed to detect machine issues
Enabled web and role-based dashboards for different employees to gain the insights they need too
Challenges and Opportunities
Acquire all information needed for process improvement and enhancement of transparency of the shop floor
Align data from production resources with business processes
Enable enforcement of measures to optimize flexibility, efficiency and effectiveness of the plant floor
Deliver convincing data that enables the customer to detect bottlenecks within the production and create error analyses.
