January/February 2011

The underutilization of manufacturing intelligence

By John Nesi

Today's manufacturing enterprises are global, asset intensive, and feature high-variability designs that make them difficult to manage from an operational perspective. From a business perspective, executives are faced with a number of challenges, including the rising costs of raw materials, energy, and compliance measures. Simultaneously, recent economic conditions have forced companies to seek out new opportunities for saving money and boosting their bottom lines. Together, these challenges can seem insurmountable; however, manufacturing intelligence can improve insights to create a demand-driven environment manufacturers need to achieve success.

Manufacturing intelligence is the strategy for turning automation control system-level data into actionable information that is visible and useful to people throughout the value chain, including sales, supply, and logistics. Effective manufacturing intelligence applications seamlessly share relevant data from maintenance, quality, and operations systems, and the critical, time-series data from automation and control systems in a single environment. 

Businesses are discovering harvesting data that has been left dormant and isolated in disparate controllers, human machine interfaces, and other plant floor systems can provide vital information about overall equipment effectiveness, system uptime, energy use, and other key performance indicators. To harness this data, companies must overcome the barriers to collecting, correlating, visualizing, and sharing plant floor information with the overall operation.

Rockwell Automation recommends a systematic approach to enable manufacturing companies to build this capability.

Step 1: Evaluate data storage areas

Manufacturing companies employ a variety of information systems to allow employees to accomplish their operational tasks. For example, machine operators, maintenance personnel, and plant managers each focus on different aspects of plant operations. Organizations must take note of the needs in each department and the systems in place that are currently used to gather and share this data.

Step 2: Integrate disparate data

To aid data integration, manufacturers should consider leveraging the following:

  • Industry standards and a unified production model (UPM) that provide a cohesive view of seemingly disparate manufacturing data and give context for relationships among equipment, product, materials, and people. The UPM organizes various manufacturing and enterprise data using commonly referenced business terms, like "equipment," "batches," or "manufacturing lots." 
  • A single control platform that can provide discrete, batch, process, safety, drives, and motion control enabling plant-wide control and optimization.
  • Modeling and simulation solutions that factor in energy and raw materials as variables for optimizing profitability.
  • Open networking standards, such as EtherNet/IP, to help ease data transfer from field instruments to the enterprise level.
  • Modern software tools to access, aggregate, and correlate information, and then present it as dashboards, reports, and charts via standard browsers.
  • Wireless devices to allow for greater efficiencies in remotely accessing data.

Step 3: Leverage the results

Once data is aggregated, stored, and analyzed, manufacturers can begin to see clear trends among various historical events, such as a specific product cycles or seasonality. Using knowledge provides immediate benefits and also promotes future improvements. In other words, understand and take action.

Also, forward-thinking manufacturers are working toward programs to empirically tie consumption requirements to the production bill of materials to make proactive operating decisions.

Utilizing manufacturing intelligence allows global enterprises to make more effective decisions that deliver the productivity and profitability required to compete successfully.

ABOUT THE AUTHOR

John Nesi
Vice President, Market Development, Rockwell Automation

Nesi joined the company in 1980 as a system startup engineer for the Drives Systems Division of Reliance Electric and has held positions of increasing responsibility in service, operations, channels, sales and product marketing. He most recently has taken broader scope for the Rockwell Automation company wide marketing efforts around market development, strategic marketing and vertical industry marketing. Nesi earned his bachelor degree in Electrical Engineering from Cleveland State University in 1980 and is an executive scholar of Kellogg School of Management.
janesi@ra.rockwell.com