How To Create a Continuous Improvement Feedback Loop With Smart Manufacturing Technology
Learn how to use smart manufacturing technology to create a continuous improvement feedback loop that will improve your production processes.
Written by
O3ai
Published on
March 2, 2023
In the world of manufacturing, the ability to quickly and accurately measure and analyze data is critical for ongoing success.
To stay agile, companies need to use lean methodology techniques such as continuous improvement feedback loops which leverage data to identify problems, set goals, and monitor performance over time.
In this article, we’ll discuss how smart manufacturing technology can be used to create a valuable continuous improvement (CI) feedback loop that generates insights to improve efficiency, boost productivity, and increase profitability.
What is a continuous improvement feedback loop?
A continuous feedback loop is a data process that allows manufacturers to constantly measure and improve the effectiveness of production processes across their operations.
Gather Data – Apply IoT sensors that are placed on the production line and machinery to capture real-time data on performance and usage. The data is automatically captured and sent to the cloud for storage. Supervisory Control and Data Acquisition (SCADA) systems can also be used to monitor and control industrial processes and capture data.
Analyze Data – Data can be fed into a digital twin model that processes it into a meaningful format. Alternatively, less powerful methods can be used, such as MES and MOM systems. The O3ai platform has built-in digital twin models that can be selected and adapted to suit any type of manufacturing operation.
Generate Insights – Visualizations such as graphs, charts, or color-coded alerts can be automatically generated from the real-time data provided in the digital twin model. Insights can be generated by either examining the visualizations or using AI and machine learning engines. The virtual model can be used for insights into predictive maintenance, process optimization, quality control, energy management, waste reduction, and remote decision making.
Implement Changes – Once areas for improvement have been identified by studying the generated insights, the next step is to develop a plan and implement the changes over a specific timeline. For instance, a manufacturing company may realize that a certain assembly line machine has more downtime than average and they can implement a program of autonomous or preventive maintenance to reduce the failure rate.. If used in conjunction with AI, a more accurate maintenance schedule can be created that will make sure repairs are done at the appropriate time.
Evaluate Results – Manufacturers can set up KPIs and KPI monitoring using a smart manufacturing platform module (such as O3ai). Managers can monitor KPIs that are relevant to the implemented changes, for instance machine downtime, energy consumption, or production efficiency. Other evaluation methods can be used such as comparing the actual results with simulation projections or running a cost-benefit analysis.
The continuous improvement feedback loop can be applied indefinitely, as new real-time data is constantly fed in which can be analyzed. From this insights can be generated and improvements planned and implemented.
One of the main things to get right when setting up a continuous improvement feedback loop in manufacturing is ensuring reliable connectivity and facilitating clear communication of data.
Applying smart manufacturing modules to create a continuous improvement feedback loop
O3ai’s modular smart manufacturing platform provides the ideal foundation for a successful data feedback loop. To set it up successfully, we recommend that you implement the following modules as the initial building blocks:
Productivity Management – Use a digital twin to automate data capture and processing from machinery and shop floor activities. Identify inefficiencies, increase productivity, and reduce losses across your operations.
Production Order Management – Automate your production order processing for more reliable and faster order fulfillment.
Autonomous Maintenance – Empower operators with more accurate and paperless inspection and maintenance schedules to reduce machine downtime.
KPI Management – Evaluate the success of improvement interventions with automated data capture and insight enablement for KPI management.
Quality Control Management – Monitor quality with automatic data capture and alerts to reduce flaws and losses.
Key takeaways
Setting up and maintaining a continuous improvement feedback loop can help you to become a manufacturing powerhouse that is constantly driving up efficiency and productivity.
A continuous feedback loop consists of – data capture, data analysis, insight generation, change implementation, and evaluation of results.
The key to a good CI feedback loop is a solid smart manufacturing foundation to automate data capture, data processing, and monitoring.