Making remote support work in manufacturing

Oct. 24, 2023
Businesses that want to reap the benefits of this model must understand its specific challenges and invest in the right technology to help them overcome these challenges.

In recent years, the debate surrounding the effectiveness of remote work has shifted from skepticism to acceptance. What is clear now is that, for a wide range of industries and professions, the traditional physical office is no longer the sole path to success. Workers and companies are increasingly embracing the idea of fully or partially remote work, recognizing its potential to reshape the way we define and experience work.

Intuitively, people understand why remote work is possible for programmers or communications professionals, but some are still surprised to learn that hands-on manufacturing fields can also benefit from remote support. There will always be a need for on-site field staff and control room operators; however, support staff, engineers and data scientists can be moved off-site. From oil and gas companies to chemical facilities and power plants — the benefits of working remotely are hitting every industry.

These benefits — which include enhanced productivity and efficiency, as well as greater cost-effectiveness — can substantially impact a business' bottom line. But they do not come automatically. Businesses that want to reap these benefits need to do two things:

  1. Understand the specific challenges inherent to remote support in manufacturing
  2. invest in the right technology to help them overcome these challenges

The challenges of remote manufacturing support

Let's start with the challenges.

To start, every manufacturer faces a common problem, regardless of their operational location: the challenge of gaining a clear and detailed understanding of what is happening at their facility.

The fact is that even a small facility will invariably produce more data than it could ever hope to handle manually. Often, this data will be dispersed across several often-incompatible systems and streams: Laboratory Information Management System (LIMS), Manufacturing Execution System (MES), Enterprise Management Software (EMS), Enterprise Resource Planning (ERP) tools, shift logs, process data and more.

When this information is siloed, processes are slowed and employees have to log in to each system individually, suffer through data delays and — if the technology even allows for it — manually collate reports. Accordingly, employees are often forced to make important decisions while operating partly in the dark about their own facilities — a process not likely to engender optimal outcomes.

Then there are the inevitable security issues. Remote work (and the rise of multi-cloud generally) has led to a proliferation of vulnerable endpoints and created far more opportunities for savvy hackers to work their way into undefended systems.

Of course, the impediments to getting remote manufacturing support off the ground at any given company are not merely technological. In many sectors of the manufacturing industry, there remains a real resistance to change — there are facilities whose engineers have done things more or less the same way for years and who will scoff at any effort to overhaul a system that they believe already works.

Overcome these problems through digital transformation

These are significant challenges and daunting ones. At the same time — especially given recent advances in technology — they are also eminently manageable.

The major innovation here — the one that has effectively changed the face of remote manufacturing support — involves industrial analytics software. In recent years, industrial analytics and visualization software has evolved to the point that a single server, plugged into multiple data systems, can permit relevant stakeholders to monitor and support all process operations through a single log-in. LIMS, MES, EMS, ERP — merge into a single, intelligible stream. Employees can engage in data-related tasks like data access, unit monitoring, and root cause analysis anytime, anywhere, and without the endless delays that have plagued manufacturing systems for decades.

Of course, making this work for your facility will inevitably mean a robust investment in cybersecurity — in network security monitoring tools, in encryption tools, in antivirus software and packet sniffers, and managed detection and response services. In this unprecedented, relentlessly intensifying threat environment, skimping on any single component of a robust cybersecurity plan can spell disaster — even if you have no intention of switching to remote manufacturing support. And these investments should, of course, be accompanied by employee training to help guard against ransomware attacks and other social engineering methods.

Which leaves us with one last challenge to overcome: the resistance of employees attached to doing things the old way. The best approach here is to simply show these people what today's data visualization tools are capable of — to sit them down and walk them through the live plant data, the dynamic, big-picture displays and the automated charts and reports. Often, that is more than enough to change their minds.

Either way, of course, they are going to have to change their minds eventually because, at this point, the conclusion is inescapable: remote work is the future. Holdouts hoping that things might return to the office have been roundly disappointed; workers prefer it, and their employers do, too. Not every manufacturing company has gone the remote route yet, but most eventually will, which means that if you haven't made the change yet, there’s no better time than now. 

Kevin Jones serves as the director of sales and marketing for dataPARC. He has been with the company since 2001 and has more than 22 years of experience in process industries and using data to drive decisions. Kevin holds an undergraduate degree in chemical engineering from University of Idaho.  dataPARC is a leading provider of industrial analytics and data visualization tools for process optimization and decision support.

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