Manufacturers across industries struggled to respond to the COVID-19 crisis, illustrating the need for real-time insights, flexible production processes, and better visibility to compete effectively in a challenging business environment. Manufacturers must capture and leverage data to help them get the most out of their facilities. But, they are facing limitations in their ability to forecast demand and improve quality continuously. They need better analytics solutions to uncover critical issues and drill into root causes. More importantly, many are managing multiple sites across different geographies, typically with aging equipment that’s becoming increasingly expensive to run and maintain.
There is a solution to these challenges, and it’s not as difficult as you think. Based on our long experience working with manufacturers across several industries, the answer lies in collecting and analyzing data in real time. Advanced analytics can help you understand your operations and improve your plant performance in unique ways.
How Manufacturing Analytics Can Improve Plant Performance
Get Deeper Insights
First, you must be able to collect data from disparate manufacturing systems across your business, for which you need standards-based interfaces. Next, you must gather digital signals from operational technology controls, IoT devices, human-machine interfaces (HMIs), and other information sources in local plants. You must store this data in a centralized location in the cloud that will give you plant-specific and org-wide insights – i.e., complete visibility into all your shop floors.
Make Accurate Forecasts
Supply chain disruptions and unexpected demand shifts make forecasting more challenging. You can no longer rely on past experiences to plan future production schedules. Manufacturing analytics can deliver predictive insights to help you plan better and offer solutions to detect hidden patterns in your data. It can help you transition from reactive to proactive planning and keep your planning aligned with your operations.
Identify Critical Challenges
Different functions in manufacturing, such as finance and engineering, collect different types of data. Or they analyze the same data set to reach separate conclusions. You must standardize your raw data, ensuring greater accuracy, relevance, and continuous process improvements. Manufacturing analytics enables you to find the root causes of issues such as unscheduled downtime and performance losses. Advanced analytics powered by machine learning algorithms can accelerate such root-cause analysis, providing predictive capabilities that drive production output and efficiencies.
All your key stakeholders must be able to analyze performance drivers at the plant level and across your operations to improve product quality. The ability to collect, standardize, and analyze data to measure your performance against KPIs is critical. You must use industry-standard KPIs or create your own KPIs, using specialized tools to integrate industry measurements such as overall equipment effectiveness (OEE). Additionally, it’s essential to generate self-service reports with customizable views so stakeholders can visualize, understand, and track KPIs and live operations data.
Optimize Aging Plants
Manufacturers struggle to minimize downtime, reduce waste, and increase ROI in physical assets. Manufacturing analytics can help you keep older equipment working effectively by providing insights to improve efficiency, production rate, and yield across your manufacturing locations. You can reduce production costs, resulting in lower overall costs (both CAPEX and OPEX). Applying cutting-edge technologies like advanced analytics, IoT, RPA, and machine learning can help you increase visibility into your processes, improve decision-making, and maximize ROI.