The biggest hurdle for most manufacturing and processing facilities isn’t accepting the idea that connected devices and systems can improve operations and business performance. It’s the question of how to implement the necessary technologies and procedures within an existing facility populated with systems that pre-date the Industrial Internet of Things (IIoT) and Industry 4.0 concepts.
To help companies better understand how to facilitate this change within their existing plants, Spencer Cramer, CEO, ei3 Corp. (a provider of IoT platform technology) and John Kowal, director, business development, B&R Industrial Automation (an automation hardware and software supplier) have authored a white paper for the Industrial Internet Consortium that explains how a concept from the 1970s, known as The Focused Factory, can be successfully applied today to create an IIoT “green patch” in a brownfield plant.
The Focused Factory concept revolves around the idea of creating a factory within a factory. It is a greenfield operation comprised of full-scale manufacturing systems, lines, and/or cells that are intended to be used in production indefinitely. The equipment, tooling and operational and information technologies in this Focused Factory should be new, up-to-date technology. Cramer and Kowal note that with a well-defined scope, this project becomes “a manageable, measurable proof-of-concept project that pays for itself before scaling up.”
Though it may sound like a pilot project, that title does not fully describe the Focused Factory. In their white paper, Cramer and Kowal list several criteria for creating an IoT green patch project that helps explain why the Focused Factory is more than a pilot. That list notes that the Focused Factory should:
- Encompass a new product line or process that requires capital expenditure (capex) investment, providing a built-in cost justification.
- Focus on high value, complex products where IIoT can make a significant dollar impact on yield.
- Be an application that will benefit from flexibility, e.g., high variability/low volume, batch-of-one manufacturing with short lead times and/or anticipated product modifications and options.
- Be an operation where maximum uptime is essential and that will benefit from predictive maintenance.
- Have a manageable scope, i.e., a production line or cell that can effectively be self-contained and operate independently from the rest of the factory, with components or materials sourced as if the factory is an external supplier.
- Be capable of being isolated, e.g., leveraging an MES or ERP system hosted on premise to eliminate IT security issues and develop a flattened IIoT network hierarchy to provide a direct connection between machine-to-cloud, edge and machine-to-machine that might otherwise be too ambitious.
To provide success metrics for this green patch, Cramer and Kowal suggest using Overall Equipment Effectiveness (OEE) and Total Productive Maintenance (TPM). The authors note that the green patch “can be used to redefine a consistent OEE metric moving forward, for how and what to measure, analyze and optimize in the green patch, and therefore serve as a framework for OEE future process improvements without impacting existing operations.”
In this green patch scenario, TPM is seen as a way to leverage OEE data to improve the operation of machines and lines. As Cramer and Kowal note, “TPM is used here as an example of what to do with analytics once you have the data and you’ve analyzed it.”
In an IIoT-enabled green patch application, process optimization using TPM can address far more factors than it has historically been used for because more conditions can be monitored more effectively in a connected IIoT environment. Examples of new applications for TPM in a green patch include assessment of:
- Variations in material lots, material deformation and recycled content;
- Impact of environmental factors such as ambient temperature, humidity and contaminants;
- Process factors such as heat buildup, ramp-up/down to/from optimum line speed, mechanical wear, inconsistencies in electrical and compressed air supply;
- Anomalies that can be traced back to human factors, such as operation, lubrication, cleaning and improper use of e-stops; and
- Logistical issues such as parts replenishment, coding system ink level, tooling and change part availability.