They may not always get the recognition they deserve, but midsize mill products manufacturing companies- including in the paper and packaging industries - are the bedrock of modern economies.

Whether its sheet metal fabricators, plastics moulders, paper mills or packaging makers, these are the companies that few end consumers ever hear of, but who play a critical role in the supply chains of so many of the everyday products we all use.

What’s also often overlooked is that these midsized companies typically exhibit growth as strong – or even stronger –than their larger peers. In fact, by some estimates, manufacturers in the United States have outperformed some of the biggest companies in the world over the past decade.[1]

These companies should not only feel pride in their recent performance, but also positive about the opportunities for future digital transformation and innovation – both in the products they make and in the manufacturing processes they use to make them.

Indeed, their smaller size often makes them nimbler and more agile than larger competitors. So they can transform faster, gain more advantage from digital innovation, pivot to new markets more easily, and better prepare themselves for future M&A opportunities.

Cloud ERP as growth enabler

However, having the right business technology in place is a critical prerequisite. And it’s why cloud ERP is an increasingly important consideration for manufacturers of all shapes and sizes.

At SAP, we’re proud that our Cloud ERP offerings like SAP S/4HANA Cloud Public Edition are helping the world’s manufacturers solve challenges and scale up performance. An example? Take Slovarm, a specialty fitting, piping systems and plastic product component manufacturer based in Central Europe.

The company wanted to be able to respond proactively to a changing market. But its aging ERP system, cumbersome MRP, and spreadsheet-based planning was holding it back.

By implementing SAP S/4HANA Cloud Public Edition, Slovarm was able to integrate key processes and reduce its work-in-progress and final-stock inventory by 60%. It also doubled its throughput for key production programs, while giving production planning teams increased visibility across the business.

Simplify ERP in the cloud

So why is a Cloud ERP now so important for these kinds of companies? One of the key reasons is simplicity of use.

The reality of running a smaller or midsized manufacturing business is you usually don’t have dedicated staff for different functions like purchasing, planning, sales, and so on. Instead, any single employee might perform any or all of these different activities at any one time.

These generalist users have very different needs from an ERP system. Above all, they need it to be simple, fast, and easy to use. They can’t be expected to be experts in all the intricacies of a complex application. Nor can their company be expected to maintain a large team of IT experts to implement and maintain it.

That’s why a system like SAP S/4HANA Cloud Public Edition can be so valuable for these businesses. Not only do they get an ERP provided as a service in the cloud, but they also get a simple and user-friendly system with out-of-the-box dashboards showing key analytics in areas like inventory management.

On top of that, the application makes it easy to automate routine activities, such as automatically booking a sales order as soon as it comes in. So it saves employees time, improves their access to data, and increases their operational productivity.

Enable intelligent decisions

Then consider the impact on data-driven decision making. This can really benefit midsized manufacturers because it can often be difficult for generalist users to make full use of all the operational and business data at their disposal.

To solve this, a cloud ERP can provide actionable intelligence to help generalist users make more informed decisions. That even includes prescriptive insights — such as a menu of ‘what if’ simulation options – based on real-time operational and financial data.

Imagine, for instance, an employee is running MRP and sees that stock outages mean certain sales orders can’t be covered within the agreed time. SAP S/4HANA Cloud Public Edition can suggest a series of options — delaying the order, offering an alternative product, using a different material, and so on — and simulate the financial and customer impact of each one.

Visibility into fragmented data

But what about the data itself? Midsized manufacturing businesses often suffer from siloed data and fragmented systems built up over time, affecting their ability to gain insights into the true state of overall operations.

We all know what happens in practice. Without a single repository for business data, valuable insights remain trapped in spreadsheets, email attachments, physical paper, or any of the myriad other data formats used by different teams.

The impact? Inefficiency and a lack of overall visibility into how the business is performing at any one time. Again, this is a problem that a cloud ERP can solve. When all this data is consolidated in an application like SAP S/4HANA Cloud Public Edition, generalist users can not only see everything together in one place, they’re also better able to join up the dots across the business.

To take a simple example, they can see how a sales order was planned, which production orders were attached to it, when the delivery was scheduled, and when that delivery actually happened. And they can view it all through a visually appealing graphical interface.

It means employees are better placed to see issues as they arise — whether that’s ballooning costs or a customer order going off track — and take immediate proactive steps to prevent them.

Take growth to another level

These are just a handful of the benefits that midsized manufacturers stand to gain from switching to a cloud ERP solution.

From improved supply chain resilience to streamlined operations and from enhanced cost management to product innovation, there are numerous other ways to work smarter, faster, and more efficiently with SAP S/4HANA Cloud Public Edition.

To find out more about how GROW with SAP can help midsize manufacturers achieve these gains and continue their proud record of strong growth and product innovation, please take a look at our dedicated website for mill products businesses here or request a free trial here.

[1] https://www.mckinsey.com/featured-insights/mckinsey-on-books/the-titanium-economy

A Computerized Maintenance Management System (CMMS) can reside at several different levels in the automation hierarchy.  Level 2 is the first place a CMMS can have access to the instrumentation it needs.

A CMMS is intended to help maintain equipment that is used in an industrial facility. It has a database of equipment and fields to reflect what maintenance what done on each piece of equipment. There are several ways a CMMS can work:

• CALENDAR: The simplest way a CMMS can work is based on calendar. If you know how long it has been since you last checked a motor, you will know when you should schedule the next inspection. Facilities schedule outages with plans to inspect a list of equipment. Inspections can include sensor calibration, valve stroke testing, and motor inspection. You cannot inspect every piece of equipment during an outage, so you need to prioritize. A CMMS helps prioritize the work so that you can have an effective shutdown that ensures the right equipment was inspected and is in good condition until the next outage. For this implementation, the CMMS does not need to connect to anything. You are manually maintaining the data in the same way as you do in a spreadsheet on your desktop computer.

• RUNTIME: Using a calendar is a manual process that may not tell you whether the equipment really needs maintenance. If a pump has been sitting idle for months, it may not be as important to inspect as another piece of equipment that is heavily used. This usage data is typically at a level 1 device; the running hours, number of stop/starts of a motor, number or magnitude of valve strokes can be accumulated in the control device. If a CMMS system can access that data, it is extremely helpful for automatically prioritizing maintenance. That is why you connect the CMMS at Level 2 or above. If you have a CMMS at a higher level, it could be used for multiple facilities to connect to usage data. That is what the 4^th industrial era makes feasible.

• PREDICTION: With connectivity, we have data that could be used to predict failure of equipment. Predictive Maintenance is an application that has grown in adoption and greatly aids in prioritizing maintenance. Runtime alone does not tell you the whole story. If you look at data from a pump, you might detect abnormal behavior from differential pressure, heat, vibration, or a combination of variables. Sometimes you can have long runtimes on a piece of equipment, and it is perfectly fine, while an infrequently used piece of equipment is not performing well. Using data to identify abnormal conditions for the equipment can automatically prioritize the maintenance in a smarter way.

A related application is an Asset Management System (AMS). When you have digital sensors (ones that communicate by Fieldbus, HART, ProfiBus, or other protocols), there are data files that need to match the sensor to enable communication. Maintaining these data files for every type of sensor or valve can be a daunting task. An AMS helps with this task, but also can access diagnostic information and documentation that aids in maintenance. Ideally, an integrated AMS and CMMS makes maintenance much more effective.

Industrial facilities have a lot fewer onsite maintenance people than they used to have. That means these people are overworked and will takes their knowledge to a better job, or you will have equipment that you rely on being unreliable. These systems make profitable and safe operation feasible in the 4^th industrial era.

When I say "Economic Growth" that is code for jobs. But what will jobs look like and how much of our time will they take in the AI world? And will there be any room left for human creativity in the AI world?

Looking at the past, I think we can be encouraged. Henry Ford adopted the 40 hour week (down from 60 hours) and the $5 per hour wage. This gave his workers a two day weekend and the means to afford the product they were building. The assembly line, invented by Ford, was the AI of the day and the gateway to these economic improvements.

In the AI world, the wage earner will be experiencing an even shorter work week, yet have the income to afford the middle class items of today. Entrepreneurs will still work every waking hour.

The challenge will be educating the wage earners to be productive in their shorter AI week. This starts with the school system and native intelligence. In Ford's day, it didn't take extraordinary intelligence to assemble an automobile, even on an assembly line.

Today's and tomorrow's tasks are far more cerebral, much less muscular. Some people simply won't have the mental acuity to keep up with this pace. Others may have the native intelligence, but will be lacking the scholastic infrastructure to employ it efficiently.

Bottom line? More and more people will be choosing their careers earlier and earlier in order to adopt a path that works for them. Preschool will be very meaningful in order to catch the right wave. This is what I worry about in two ways. 1. Having the means to sort very young people according to aptitude while at the same time, 2. Allowing them the freedom of choice when they are of an age they don't quite yet understand what that means.

Increasing pressures such as supply chain disruptions, accelerating product cycles, the greying workforce, and increasing consumer demand for complex electronic products mean that manufacturers must do more with less... and do it faster. Manufacturing quality teams are put in a tough position; they must improve quality while maintaining or increasing production volumes.

We’ve been using artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), for many years. In fact, we use them every day for tasks such as data preprocessing, image analysis, online chatbots and driving assistance in our vehicles. All these applications use training sets and responses.

If we’re finished with the hype cycle, we’re probably talking about a technology that’s here to stay. So, when IndustryWeek asks manufacturers and analysts for their predictions about manufacturing technology in the coming year, we’re looking for the most mature technologies with the widest adoption rates.

The industrial sector has undergone a significant digital transformation in the past decade, with critical infrastructure sectors witnessing sweeping changes in supply chain management, energy management, and remote monitoring. The convergence of IT and OT systems, the rise of IoT assets, and the transition to cloud environments have unlocked many opportunities and introduced new cybersecurity challenges, including increased manual work for security teams.