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6 Keys to Digital Agility in Automation

Digital agility that comes from the effective collection and processing of plant data is the key to the success of smart manufacturing technology.

Achieving the adoption of company-wide automation creates digital agility that can cuts costs, eliminate errors, improve productivity, and increase revenue. Digital agility is especially important amid COVID disruptions since it allows manufacturers to quickly pivot and meet the moment. The core of creating digital agility is the effective use of data.

Most smart manufacturing tools gather data. Using that data effectively is the key to automation success.

According to a recent McKinsey study, “Industrial companies are making forays into digital manufacturing, but many have yet to see bottom-line results from their efforts.” Turning automation deployment into measurable results depends on getting a wide range of issues right. One of them is the ability to use data effectively.

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The success of automated manufacturing depends on getting the data collection and processing right.

We turned to Catalytic – a company that provides a platform to help companies manage manufacturing data – to find out what it takes to use data effectively. The company works on the premise that manufacturers need to get six digital processes right in order to get the most from their advanced automation systems.

  1. Reviewing Data Quality

The first principle of digital effectiveness is to make sure the data is not corrupted on its path from acquisition to analytics. “Improving downstream operations begins with clean data. When data is incorrect, missing, or outdated, a manual review and tedious rework are required,” Sean Chou, co-founder, and CEO of Catalytic, told Design News. “Effective automation needs to continuously review data proactively correct any inconsistencies, allowing all downstream processes that interact with that data to operate at peak efficiency.”

  1. Identifying Gaps, Omissions, and Duplicates

Part of the process for ensuring clean data involves systematically catching potential data problems. “Automated omission and error checks can be built into any automated process and they provide two pivotal benefits,” said Chou. “First, they free employees from spending hours on redundant manual reviews, while also eliminating the risk of additional human error. Second, they ensure that the quality of the data improves downstream. That, in turn, improves the efficiency of the processes reliant on that clean data.”

  1. Triggering a Process to Fix the Issue

Issues in the system can quickly become bottlenecks that can stymie data analytics or even production. The system needs to be able to identify problems and then assign the solution to a particular person or group.

“Triggering an automated process to track and manage issues brings visibility to potential roadblocks, streamlining cross-team coordination and minimizing downtime,” said Chou. “Whenever a new issue is identified, it can be automatically assigned to the proper person based on business function, expertise, or priority. This avoids multiple handoffs and wasted time. After an issue has been assigned to an owner, an automated process can keep all relevant parties updated on the status and estimated completion date.”

  1. Sending Smart Web Forms

A Web Form is a web application framework supported by Microsoft ASP.NET. These applications are reusable components that can be programmed to respond to events. They can be used to assess how data should be processed as it’s acquired. “Not only are smart Web Forms a way to collect survey data, they give us the ability to insert human intelligence, judgment, and exception handling into any process,” said Chou. “Plus, smart web forms streamline process communication, eliminating the need for email, while also gathering data along the way to report and analyze efficiency. In the end, this improves visibility into a process, making organizations smarter about how they work and collaborate.”

  1. Storing Customer, Vendor, and Employee Responses in a Database

Surprisingly, feedback from often stakeholders gets lost in the mix. Sometimes it doesn’t go to the right person; sometimes it doesn’t go anywhere. Yet this information can be crucial to successful automation processes. Manufacturers can set up systems to make sure this feedback gets to the right person in a timely manner. “Customer, vendor, and employee feedback provides invaluable insight into the health of a company’s processes and customer relationships. Sadly, these insights are often lost in a black hole of survey responses,” said Chou. “By storing them in a database, they are easily accessible for automated and continuous analysis. Automation can also quickly distribute those responses to the right people — turning insights into action.”

  1. Organizing Data to Make a Case for Continuous Improvement

One aspect of the automation process that often gets lost is the concept of – and the commitment to – continuous improvement. One plant manager put up a banner that read, “Remember, This Is About Continuous Improvement!” In all the discussions about new technology and all its advantages, sometimes the basic reason for the automation deployment gets lost.

“When a process feels broken, it can be difficult to pinpoint where the breakdown is occurring. Using smart web forms to gather data and store it in an accessible database makes identifying trends and areas for improvement simple,” said Chou. “Management teams can then focus their process improvement efforts and quickly help their team acclimate to new challenges.”

Rob Spiegel has covered automation and control for 19 years, 17 of them for Design News. Other topics he has covered include supply chain technology, alternative energy, and cybersecurity. For 10 years, he was the owner and publisher of the food magazine Chile Pepper.

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