Manufacturing analytics unlocks the power of real-time data, transforming the entire production process into a well-oiled machine. By harnessing advanced tools like predictive analytics and IIoT, manufacturers stay competitive, turning data into smarter decisions and driving innovation on the factory floor.
Why harness manufacturing analytics?
Manufacturers have long struggled to fully leverage data from the entire production process, from supply chain management to customer delivery. They used to rely on expensive, complex systems that could only pull data from limited sources like operators and machines. Finding the cause of production issues could take weeks. With the changing times, waiting days or weeks is no longer viable. Instead, now manufacturers aim for complete transparency through the entire process. This ranges from raw materials to end customer usage, with an objective of getting a complete view and improve efficiency levels.
In this blog, we will decipher the beaming role of manufacturing analytics in industrial operations, along with how they ensure that crucial KPIs are sustained.
The role of manufacturing analytics
A combination of technologies such as predictive analytics, Big Data, machine learning, IIoT, and edge computing are used for manufacturing analytics. A modern software such as Asset Performance X provides an amalgamation of these tools, helping companies gather real-time, actionable insights from various sources.
By collecting and analyzing data across all stages—from machinery to human input and order processing— such systems help identify issues and streamline the workflow. And by leveraging large data sets, manufacturing analytics can recommend real-time actions or automate processes based on these insights.
How manufacturing analytics works
Key benefits of manufacturing analytics
1. Reduce unplanned downtime
Sensors data from equipment can signal issues like unusual vibrations. This allows companies to perform maintenance before a major failure occurs, and keeps production lines running smoothly.
2. Boost productivity
Manufacturing analytics help companies optimize the productivity of both their machines and employees, potentially increasing profit margins. For example, Octopus Digital successfully identified significant operational inefficiencies for a major textile manufacturer by leveraging OmniConnect™ Cloud Platform. The result was a thorough increase in efficiency. This enabled the manufacturer to cut costs and boost sales through better use of resources.
3. Cost optimization
Companies can use manufacturing analytics to better understand costs associated with labor, materials, and overheads. This helps avoid excess expenses like overstocking raw materials, and improves profit margins.
4. Enable new business models
Some manufacturers now offer services rather than just selling products. For instance, an aircraft engine maker may determine how long engines run without needing repair, and charge airlines accordingly. Through manufacturing analytics, manufacturers can predict maintenance needs, and support service-based revenue models. The result is stronger customer relationships.
5. Monitor KPIs
Analytics helps track and understand the root causes of issues in plants and supply chains, affecting KPIs. This ensures that companies can flag and act quickly to fix potential problems.
Let’s take a look at the critical KPIs considered while tracking and enhancing performance through manufacturing analytics:
- Perfect order rate: Reflects how often companies deliver products without errors.
- Yield: Measures how efficiently products are made according to specifications.
- OEE: Tracks the time in which a plant has been productive in order to predict and prevent and tackle equipment failures. This is achieved by considering factors such as availability, performance, and quality.
- On-time delivery: Assesses whether products are delivered to customers, within the promised time frame.
- Throughput: Measures how efficiently products are produced within a given time.
- Cycle time: Calculates how quickly a plant can fulfill orders from the moment they are placed.
- Production volume: Looks at the total number of units produced over a specified period.
- Capacity utilization: Measures how effectively a plant matches its capacity to demand.
- Scrap rate: Tracks the amount of wasted material after production.
Using KPIs to enhance manufacturing performance
Leaders utilize manufacturing analytics to help understand the issues within each of these KPIs, along with how they relate with one another. Let’s explore the how:
1. Improving supply chain and employee productivity
To track supplier performance, manufacturing analytics play the crucial role of highlighting cost-effectiveness, and consistent on-time deliveries and product quality. It helps visualize inventory levels across their supply chain and lets manufacturers address shortages before they disrupt production. This proves quite useful for large manufacturers managing numerous suppliers at once.
Furthermore, appropriate prioritization of work orders is ensured by manufacturing analytics, so that critical projects take precedence over lower-priority ones. This allows for reduced downtime and optimized productivity for workers, along with a more strategic production process. By scheduling maintenance during equipment downtime, employees aren’t left waiting for machines to be repaired.
2. Limiting product recalls
The use of detailed equipment reports and real-time production data allows manufacturers to identify roots of issues in product quality. This reduces the scope of product recalls, lowering costs and improving customer satisfaction.
3. Granular data and reduced employee turnover
Manufacturers can drill down to individual machines and production lines to improve their KPIs. Manufacturing analytics also identify safety concerns or work conditions that could lead to higher employee turnover. Addressing these issues boosts employee satisfaction and reduces attrition rates.
4. Accurate financial reporting
Companies using manual systems to manage their financials often end up with inconsistent data. Analytics automates reporting, removing the risk of human error or data manipulation. This results in more reliable financial insights.
Role of OmniConnect™ in manufacturing analytics
On-premises systems are still used by many manufacturers, which can’t handle the data volumes of today. OmniConnect™ Data Cloud – an all-encompassing platform designed for IT/OT convergence, enables seamless gathering, processing, and analyses of data from multiple sources, including IoT devices.
By supporting real-time decision-making and predictive analytics, OmniConnect™ drives operational efficiency. Some key features are 24/7 remote monitoring, no-code integrations, Zero CAPEX, and AI/ML-driven insights to support Industry 4 initiatives. This makes it ideal for businesses that aim to leverage data for innovation and growth.
Conclusion
Manufacturing analytics are a prevailing tool, that allow companies to enhance productivity, optimize costs, and stay ahead of the competition. Leveraging KPIs and real-time data, manufacturers enjoy streamlined operations, with boosted profitability, and innovation.
If you too would like to empower your operations with the powers of manufacturing analytics, talk to our experts.
