How Calibration Software Leverages Data Analytics and Trend Analysis Tools to Provide Insights

Preventing nonconformances and ensuring products meet the specifications is key to quality control in manufacturing industries. An important cause for deviations from specifications can come from the machines used to process and manufacture the product. A well-calibrated machine is essential to maintain accuracy, standardize products, and facilitate repeatability of measurements. If it is not calibrated regularly, the output can become inaccurate, affecting product quality, safety, and performance on the one hand and equipment life on the other.

Therefore, keeping the machinery calibrated is an essential part of regular maintenance. Some of the consequences of not calibrating machinery properly include:

• Increased rejection of parts: When the machine is not calibrated, the output will be out of specs and cannot be used or sold due to quality and safety issues. Releasing such products in the market will lead to warnings from regulatory bodies in regulated industries and customer rejection, affecting brand reputation.
• Increased cost of manufacturing: When rejected parts increase, it leads to wastage and rework. This adds to the cost of manufacturing and time delays due to rework.
• Eroding brand reputation: If an out-of-spec product reaches the customer, it can affect the product’s performance, leaving customers unhappy. Product recalls, and customer complaints can add to the pressure, with a loss to brand reputation and, consequently, revenues.

Automating Calibration Management

Periodic maintenance of machines is important for ensuring the conformance of products to the specifications, longevity of the machine, and preventing unscheduled downtime that can disrupt production cycles.

To improve the efficiency and effectiveness of machine maintenance and calibration, cloud-based solutions such as ComplianceQuest’s Equipment Management can help with:

• Automation: Preventive maintenance can be scheduled in advance and communicated to all workers. This will help plan for downtime and avoid surprises or accidents due to the poor condition of the machine.
• Reliability: An automated maintenance schedule reduces the need to manually plan and track the activity and increases the system’s reliability.
• Visibility: Tracking the entire maintenance process becomes simpler with an automated system, including adherence to regulatory requirements and international standards such as ISO 9001 and ISO 10012.
• CAPA: If deviations occur, investigate the root cause and review parameters for maintenance and calibration. Initiate corrective and preventive action to prevent the problem from recurring.
• Lower Equipment Cost: With periodic preventive maintenance, the equipment’s life is improved, and smooth operations and planned downtimes are ensured to prevent unscheduled disruptions to the production process.
• Improve OEEE: Automating equipment management processes also provides access to data that helps spot trends and drive Continuous Improvements, enhancing OEE (Overall Equipment Effectiveness).
• Document: Compliance also requires proper documentation to demonstrate processes are aligned with statutory requirements. Automating the process reduces manual record creation and maintenance and frees up resources to focus on innovation and audit trails with access to calibration history.

Benefits of Data Analytics in Equipment Management

Using a cloud-based equipment management system such as ComplianceQuest provides manufacturers with data on equipment performance and gaps that can be rectified on time. This reduces the cost of ownership of the machine, unplanned downtime and lowers the risk of nonconformance.

Some of the benefits of using data analytics include:

• Risk Analysis: Regulations require businesses to use a risk-based approach to quality management. Data from the equipment management system enables businesses to capture performance trends, identify machinery repair and deviation risks, and address them promptly.
• Improve Conformance and Compliance: By ensuring the condition and quality of machinery and its performance, businesses can improve the conformance of products to specifications and compliance with internal and external standards.
• Lower Costs: Capturing trends and ranking risks helps businesses identify which risks to address first, improving resource utilization. It provides insights for making informed decisions, improves ROI, and improves overall operations.
• Training: Equipment data analytics can also reveal the operator’s skills based on the number and nature of errors coming from any machine. This information can be used to customize and deliver training courses based on need.
• Improved Audits: Access to machine-related information can also enable more insightful planning for audits of machinery and equipment to improve the processes surrounding machine usage and maintenance.
• Management Review: The data can provide the management with insights into machine usage, quality and safety issues, and maintenance data to improve management decisions related to equipment purchase and usage.