How To Leverage The IIoT And ERP To Create A More Connected Enterprise
POSTED 06/20/2018 | By: Sean Balogh
The IIoT has flooded manufactures with information like never before with valuable data from every aspect of operations. However, having data is only part of the solution. You need to be able to make sense of that data in your possession. Experiencing only a portion of the bigger picture can leave your business shortchanged on vital data necessary to make informed decisions on the future of your organization. ERP solutions, whether appealing to process manufacturing or discrete manufacturing operations, provide a way for businesses to make sense of the data new technology is revealing. Here are some ways you can leverage modern tech and ERP to optimize your operations.
Modern Maintenance: Prediction Preventing Predicaments
Utilizing modern sensing and machine learning capabilities, a true prediction is possible when it comes to maintaining your manufacturing equipment on the factory floor.
Everything from vibration, voltage, temperature, and other performance aberrations feed into analytical tools, are visualized by intelligent ERP solutions, to be translated as a set of warnings and alerts for the right set of eyes to evaluate and make a call on what action to take.
These innovative tools have proven their efficacy in reducing the instances of incidents, accidents, and breakdowns significantly. So much so, that no one can afford not to consider implementing these tools into their own operations in the near future.
Automated systems can order replacement parts if none are on-site and schedule the replacement or repair at a point resulting in minimum downtime when it comes to production.
You might be asking: well, how does this new take on maintenance affect my bottom line? Have you ever had a part break on a critical piece of equipment? What procedures are in place to replace or repair broken machinery? Intelligent and connected devices throughout the factory can set critical data point that indicates when a part is reaching end-of-life. Automated systems can order replacement parts if none are on-site and schedule the replacement or repair at a point resulting in minimum downtime when it comes to production.
That’s one example. What if an abnormally humid summer is leading to excessive heat in the workspace as well as moisture? Maybe a crucial machine is shutting down intermittently, requiring a manual restart in each case that can take a significant amount of time. You may not have known it was faulty wiring on a portion of your factory without the insight your connected devices provide. It all boils down to getting the full picture and assuming full control. A robust ERP coupled with the IIoT in a connected factory can deliver exactly that for greater efficiency.
Mastering Agile Operations For Your Enterprise
With an increasingly global reach for many companies, remaining connected to bases of operation near and far is of critical importance when it comes to remaining efficient.
Properly segmenting data sets to be fed to the appropriate overseers is just one more invaluable capability of a connected enterprise.
For decades, the idea of centralized control has prevailed in energy, resources, and telecommunications industries. This philosophy is just as easily leveraged in optimizing performance in tandem with the IIoT. When it comes to manning the helm digitally, for instance on an offshore oil platform, the keyed-in, land-based operations center can communicate with their off-shore counterparts and even manipulate controls remotely with an interconnected series of software and instruments.
However, all the data being fed into a central hub from global operations can be too much for one pair of eyes. Properly segmenting data sets to be fed to the appropriate overseers is just one more invaluable capability of a connected enterprise.
Cooperative Communication And Collaboration
Organizing your internal operations is just as important as external components. That means putting the right people in the right space with the right information at their disposal.
Operating an enterprise comprised of siloed departments utilizing disparate systems is one of the biggest causes of problems in operations and one of the best reasons to switch to a unified ERP solution. These digital hairballs cause hiccups, miscalculations, bottlenecks, and so many more problems that enterprises refusing act before it’s too late find themselves gone the way of the dodo before long. Putting everyone on the same page with a clear channel of communication and access to the data they need is essential to organizational success.
A robust ERP solution works to empower small teams at just about any scale and with the same tools global conglomerates utilize to place, ship and trace orders, manage and store inventory, invoice, and store useful data.
Not positioned for global expansion just yet? The same tools can be leveraged to more efficiently organize local teams and their work. In this case, organize your teams so that related roles are close to each other and don’t have to go across the room, hall, or floor to get to the person or people they need to speak with to get the job done right and right now. A robust ERP solution works to empower small teams at just about any scale and with the same tools global conglomerates utilize to place, ship and trace orders, manage and store inventory, invoice, and store useful data.
One Buzzword To Rule Them All: AI
While the term has been tossed around more than a golf ball in a dryer, AI is inseparable from any conversation regarding Industry 4.0 and the modern manufacturing process. It relates to machine learning and offers numerous opportunities to refine processes using technology that can not only tell you why what was done was done, but also the rules followed to reach the solution. AI is connected to machine learning in the sense that all AI is machine learning, but not all machine learning is AI, but Don’t let that throw you through a loop. Let’s break it down.
An everyday example of machine learning involves something just about everyone uses at work, home, and at play: Email. As a means of communication, it’s is one way we all stay in touch through every aspect of our daily life, from reaching out to loved ones, co-workers, friends and services we hold valuable. Services like Google and Microsoft’s Outlook use powerful machine learning to identify core components of these messages and serve them to us with a high degree of accuracy when it comes to relevant content. It is estimated that Google’s machine learning algorithms are capable of filtering 99.9% of spam email from our inboxes. Beyond spam filtering, categorizing importance is another feat that machine learning tackles skillfully. By incorporating who we communicate with most, be it a person or a service, machine learning delivers messages of importance to ensure vital communications don’t have an opportunity to slip through the cracks. These technologies have been around for years now, but the latest from Google has really been a time saver for many. Smart Replies enable lightning-fast response to emails through the use of machine learning. By “reading” text for certain keywords and phrases, Google’s machine learning algorithms can generate a series of smart replies to send with the tap of a finger or click of a mouse button that speak directly to your conversation’s content.
AI is inseparable from any conversation regarding industry 4.0 and the modern manufacturing process.[/caption]
As for AI, recent discussions among groups and individuals have focused on Facebook. Both timeline feed and facial recognition AI have earned the social media giant the lion’s share of attention. An AI that omits certain bits of content in favor of others to deliver a more personalized experience has earned the company both accolades and ire. Facebook employs facial recognition, a powerful technology used to tag friends in photos posted on user profiles. However, the practice has been a contentious one that results from concerns over the collection of non-user data. Amazon’s Rekognition is a similar deep learning-based image and video analysis tool that the company says can detect, track, and analyze faces for a number of applications. However, it’s capabilities don’t end there, the software can also “identify objects, people, text, scenes, and activities, as well as detect any inappropriate content” according to Amazon.
While on the subject of Amazon, further everyday examples of AI emerge with AI-powered assistants, like Alexa, which accepts voice commands to create to-do lists, order items online, set reminders, and answer questions (via internet searches). Microsoft and Google also have iterations of AI assistants with Cortana and Google Assistant, respectively.
How AI And Machine Learning Fit Into An ERP Solution
The short answer is that they don’t. There is no direct communication between machine learning and ERP software. The two mechanisms exist as separate but necessary components of running a successful modern manufacturing enterprise. While machine learning can lend insight into how machines perform and how processes can be improved, proper ERP solutions provide the tools to communicate between departments, assign tasks to the right labor pools, and ensure the raw materials are there for the automated factory and its modern machinery to utilize. The unified system speaks to every department and presents the necessary data to make informed decisions for today, tomorrow, and far into the future.
About Encompass Solutions
Encompass Solutions, Inc. is an ERP consulting firm and Epicor Platinum Partner that offers professional services in business consulting, project management, and software implementation. Whether undertaking full-scale implementation, integration, and renovation of existing systems or addressing the emerging challenges in corporate and operational growth, Encompass provides a specialized approach to every client’s needs. As experts in identifying customer requirements and addressing them with the right solutions, we ensure our clients are equipped to match the pace of Industry.