Excellent supply chains begin with excellent internal operations. Defining key metrics such as cycle time, part counts and usage, then tracking this data, helps leaders benchmark performance and more effectively manage supply and demand. Unfortunately, with manual tracking, recording and analysis, data is often outdated, biased, and full of errors and gaps that can result in poor decision-making. When internal operational data is flawed, it’s difficult to accurately procure material and deliver finished goods on time. Even with automated data-collection solutions in place, leaders may be lost in a sea of data that does not provide insight or value. To turn this sea of data into usable, scalable and value-added insights, it’s essential to operationalize internal data. This means turning abstract concepts into measurable observations.
Connect the shop floor
Manufacturing equipment and shop floor operations generate millions of data points. This volume becomes overwhelming when left in its raw state. Connectivity platforms enable manufacturers to operationalize this data by capturing data from sensors, programmable logic controllers (PLCs) and machine control, then sending it directly to the cloud for cleaning and organization. Edge computing devices can also be deployed at the machine level and work through nodes in an edge network to partially process data prior to sending it to the cloud.
After it's collected and standardized, the data is then standardized into a common model with edge device compatibility. Some is sent directly to the cloud, some is partially processed, and some is immediately actionable, further supporting control and automation of equipment at the source.
Operationalized data allows operators, technicians, managers and executives to act on insights generated from the shop floor. Some of the ways manufacturers can use operationalized data include:
- Production visibility — real-time data about production allows operators and managers to quickly respond to issues and improve factors including downtime, quality rejects and equipment lifespan.
- Machine condition monitoring — by monitoring the condition of machines, companies can develop predictive maintenance strategies to extend the lifespan of assets, reduce spare part costs and intervene before problems occur.
- Supply chain control — accurate data on setup and cycle times, efficient training and standard operating procedures, and improved schedule attainment can help manufacturers better plan and meet production goals.
- Bottleneck analysis — operationalized data can be used to identify and address bottlenecks in processes, such as those related to material staging, operator performance, facility layout and other issues.
Analyze operationalized data
Structured and contextualized data provides manufacturers with valuable insights. This operationalized data, which is stored in a centralized cloud platform, can be analyzed and made available to other systems for further context. The quality of the data and the insights it generates can improve the performance of connected systems, such as business intelligence tools, manufacturing execution systems, enterprise resource planning solutions, computerized maintenance management systems and other supply chain management software.
Operationalized data also benefits teams in production, maintenance, quality, planning and supply chain. By breaking down silos and creating a single source of truth, operationalized data enables real-time, data-driven decision-making, which can help improve processes in multiple areas. This data can lead to more efficient and effective operations, ultimately helping to drive business efficiency and successful supply chain planning.
Master internal operations with data
Measuring and optimizing the internal supply chain is crucial. Traditional methods of data collection, such as manual tracking and analysis, often result in inaccurate, outdated and biased data that can leads to flawed decision-making. Industry 5.0 technologies, such as the industrial internet of things (IIOT), allow manufacturers to capture and operationalize data from the shop floor to better understand performance and drive operational excellence. By using connectivity platforms to collect and standardize data, industry professionals can make real-time, data-driven decisions that improve efficiency and ensure that supply chain management reflects actual internal operational performance.