Challenges:

Component manufacturers track the efficiency of their equipment by measuring Overall Equipment Effectiveness (OEE) which is a combination of machine availability, performance, and quality. Very often, assembly lines are composed of heterogeneous machines that perform specialized tasks. These machines are usually not connected i.e., while critical parameters that govern the operation of a machine and the information that a machine produces about its own performance is not collected and analyzed. Very often manufacturers would use manual methods to calculate the OEE of a machine which resulted in the following issues: 

• The process is manual, time-consuming, and costly.
• The process is carried out infrequently thus ‘real’ data is not available.
• Data is inaccurate, outdated, and prone to human errors.
• There is the inability to react to efficiency trends in real-time due to a lack of real-time machine data.
• The Lack of historical trends meant that future throughput trends could not be predicted.
• No visibility on how machines are utilized machine downtime costs millions.

Solution:

• Based on the automation capability of plant data will be extracted from machines (PLC/SCADA). It will be conditioned for required analytics.
• If need be retrofitting with resilient sensor appliance for data handling. The appliance consisted of a compute element and electrical sensors that will directly sense operations being performed on the machines. The events include job start and stop times as well as idle time on that machine.
• These events were securely transmitted to the IoT cloud platform which would aggregate this information and run analytics.
• Building custom visualization dashboards for the various stakeholders in the company.
• Overall visibility of machine utilization at the plant level helped supervisors plan and optimize their production schedules.
• Using this data, plant supervisors can make in-process checks on throughput and equipment efficiency and take corrective actions.
• Management can utilize long-term trending data to plan improvements to the line plan maintenance schedules and forecast for the long-term.

Architecture

Benefits:

Improved OEE

• Ability to allow both internal and external users to access the application without downloading any software ability to interface with the existing data warehouse application.
• Ability to incorporate automated routing and notifications based on business rules.
• Improvement in Machine Utilization - By viewing details on how your machines are operating, down to the milliseconds, customers can now plan their production and their maintenance schedules optimally.
• Visibility into top 10 reasons for machine downtime - track machine downtime to the last millisecond. By providing idle-time reasoning, customers can focus on the top reasons for reduced production daily and immediately correct them.
• True OEE (Overall Equipment Effectiveness) Calculation - OEE is now being calculated automatically with no manual intervention. This forms a benchmark for any process improvement initiatives on the assembly line. This forms a benchmark for any process improvement initiatives on the assembly line. Line owners can directly view the impact of an initiative and make a decision.