How Do You Streamline Manufacturing Processes Using a Machine Monitoring Software?

With increasingly complex supply chains, unanticipated disruptions, and a volatile global economy, the global manufacturing industry has experienced many challenges over the past few years. The rapid pace with which advanced production technologies have taken over factories has left little time for manufacturers to catch up. What’s missing in this landscape is an integrated approach that helps manufacturers build an industry 4.0 smart factory by leveraging new-age machine monitoring systems for better visibility, control, and forecasting abilities. In this article, we will discuss how integrating the operations of the shop floor with the broader supply chain using machine data can benefit your manufacturing business. We will also explore how iDataOps, Rawcubes’ advanced machine monitoring system, can help in collecting, analyzing, and monitoring machine data.

Collecting and analyzing shop floor data for higher efficiency

Machine monitoring systems can play a pivotal role in integrating the shop floor with the supply chain. By using smart sensors and PLC systems for automated data collection that provides real-time monitoring of production, inventory levels, machine performance, and output, manufacturers can optimize the production process and save costs. This data can aid better decision-making, streamlining of production schedules, and responding to changes in demand or supply. Here are some specific benefits of using machine data monitoring to integrate the operations of the shop floor with the supply chain:

Real-time visibility: By collecting and analyzing real-time data from machines, manufacturers gain enhanced monitoring and visibility into their production processes. This helps identify bottlenecks, optimize production schedules, and make the production operation more agile. Having better visibility of the shop floor can also identify and resolve production problems more quickly, improve efficiency, and reduce wastage of raw materials. For instance, with iDataOps, you can integrate data from different equipment and protocols across the shop floor for real-time remote tracking of machines. You can also optimize production schedules by considering factors such as demand, inventory levels, and machine availability. This can help improve efficiency and reduce costs.

Predictive maintenance: Machine monitoring systems can be used to predict potential maintenance or efficiency issues well before they lead to breakdowns or downtime. This can help manufacturers avoid unplanned downtime and improve overall equipment efficiency. For example, iDataOps, Rawcubes’s machine data monitoring tool, can help you align machine catalogs, service providers, and machine data with asset maintenance management and predictive maintenance capabilities to alert production staff and technicians for scheduled check-ups. Through automated data collection, you can also view valuable metrics like predictive remaining useful life (RUL) and mean time to failure (MTTF) to get advanced insights into the operability of connected equipment.

Quality control: By sharing data on production processes and metrics, manufacturers can identify and address quality issues early on. Machine monitoring systems can be used to monitor quality control processes and identify potential defects before they disrupt the manufacturing process. This can help manufacturers improve the quality of their output and reduce the number of rejects. With iDataOps, you gain the ability to make smarter business decisions by leveraging turn-key predictive machine analytics solutions without the need for cumbersome data integrations.

Collaboration: Insights from machine data monitoring can be shared with suppliers and clients to improve cooperation and coordination throughout the supply chain. This can result in reducing lead times, increasing inventory management accuracy, and ensuring that products are delivered on time and as per forecast. By having access to machine data monitoring tools, manufacturers, service providers, and suppliers can make better business decisions about production scheduling, inventory management, and other aspects of the supply chain. For example, the fully integrated overall equipment effectiveness (OEE) dashboard and control center in iDataOps can help you manage performance, uptime, avg. oee, raw material used.

Decoding machine data can be a powerful tool for integrating the shop floor with the overall supply chain operations. By collecting, analyzing, and sharing real-time machine data, manufacturers can run their operations at near-optimum efficiency and reduce costs. Similarly, by quickly responding to challenges or changes in business requirements, manufacturers can stay ahead of the competition by avoiding disruptions to their operations.

The integration of machine monitoring data with the shop floor and the supply chain might seem like a complex process, but it can be a valuable investment for manufacturers to build a futuristic Industry 4.0 smart factory. Many existing machine monitoring providers offer turnkey solutions that fail to integrate with legacy systems, thereby resulting in ineffective results or siloed data processes with unusable metrics. iDataOps provides a more pragmatic approach to this problem by customizing the integration process across the entire manufacturing process.

Also, remember that turnkey solutions come with their own management and analysis tools which will require data to be collected, stored, and processed in a certain format. This may put the onus on the manufacturers to adapt to these requirements. For example, they might be required to modify existing data collection processes or invest in new technology. This can get very expensive and disrupt existing processes, such as production.

Leveraging the advanced capabilities of iDataOps, manufacturers can improve their efficiency, profitability, and competitiveness. This is because machine data monitoring can enable them to share valuable manufacturing data across the organization to derive insights, which would have otherwise remained segregated.

Integrating the shop floor with the supply chain: Examples and benefits

Here are some specific examples of how real-time remote tracking of machines through machine monitoring systems can be used to improve manufacturing processes in industry 4.0 smart factories:

• A complex manufacturing process, like that of automotive components, can use real-time sensors to monitor the performance of different machines. This data is used to identify potential problems before they lead to breakdowns and ensure quality in each process and part, which helps the manufacturer avoid unplanned downtime.
• Manufacturers can use real-time data sharing to monitor the temperature of their machines throughout the production process. This automated data collection capability ensures that machines work in the optimum temperature range, preventing untimely wear and tear.
• A textile manufacturer can use real-time remote tracking of machines through sensors to track the power consumption of different machines. In addition to tracking overall performance, this information can help quantify the eco-friendliness of various products.

These are just a few simple examples of how real-time remote tracking of machines and data sharing can be used to improve manufacturing processes. With iDataOps, Rawcubes’ advanced machine monitoring, you can improve the efficiency and profitability of manufacturing operations to enjoy the following benefits:

• Real-time monitoring of production processes: To identify and address problems early on, such as machine downtime or quality defects.

• Real-time collaboration between different departments: This improves inter-departmental communication and coordination, which can lead to faster production times and lower costs.

• Real-time monitoring of the supply chain: To identify and mitigate risks, such as delays or disruptions, and ensure a high level of output consistently.

Using machine monitoring systems for data collection and analysis

Machine monitoring systems like iDataOps are critical for improving manufacturing efficiency. By collecting and analyzing data from production machines, these, machine data monitoring systems can help manufacturers identify and address problems early on, optimize production schedules, and improve overall equipment effectiveness. It’s also important to note that the deployment process for iDataOps is around 2 weeks, including data integration, augmentation, and conformity. While the typical deployment of such systems can take several months, Rawcubes team works with each client to create specific systems based on existing data architecture and technologies.

Here are the measurable benefits of using machine monitoring systems like iDataOps in optimizing the manufacturing process:

• Improved uptime: Machine monitoring systems can help identify potential problems before they lead to downtime. This can help manufacturers increase machine uptime, which can reduce costs and minimize disruptions.

• Centralized dashboards: Interactive dashboards that provide insights across the entire manufacturing process unify siloed manufacturing processes and enhance conformity across machines and the plant floor.

• Reduced waste: Machine monitoring systems can help manufacturers to identify and reduce waste in their production processes. This can lead to lower costs and improved profitability.

• Improved quality:Machine monitoring systems can help manufacturers identify and improve quality issues early on. This can help reduce the number of rejects and improve client and customer satisfaction.

• Improved safety: Machine monitoring systems can help manufacturers improve safety by identifying potential hazards and taking timely corrective action. This can help in preventing accidents and making the manufacturing site a safer workplace.

• Demand forecasting: It becomes easier to forecast demand when comprehensive historical data about performance, output, and efficiency is available for analysis through automated data collection.

• Reduced lead time: With enhanced machine efficiency, reduced downtime, and streamlined assembly, the lead times become leaner and more predictable.

The use of machine monitoring systems to optimize the production process and rationalize costs is set to rise steadily. Organizations that wish to stay ahead of the curve and build a sustainable, future-proof manufacturing business must take note. To learn how you can turbocharge your manufacturing facility with iDataOps’ advanced capabilities, get in touch with us today.