The introduction of cloud (specifically Software as a Service or “SaaS”) has had a profound impact on the methodology that organizations use to roll out software. The speed and scale that SaaS moves across a company is unprecedented and so much so that it is difficult to even compare to previous non-SaaS projects. So the question is, how can paper producers and converters also take advantage of this software paradigm shift without introducing risk to the stable operation of their plants?
Cloud has some obvious advantages when compared to traditional software, most notably it provides these value drivers which are all built into the SaaS pricing as part of the software design paradigm:
- Experts (not on your payroll) that maintain and manage the hardware, disaster recovery, and networking infrastructure
- Automatic software updates and maintenance of the platform and application(s)
- Centralized configuration and management of applications
Ability to securely access the environment from all devices without punching a hole in the corporate firewall
Options to federate out applications and processes that are defined and managed in cloud but run locally at the edge (aka fog) layer
These value drivers are important because in the past the deployment of new software meant that there was a large amount of overhead to not only manage the initial setup, but also to control the variations and configuration nuances that occurred over time. These expenditures are the hidden cost of software that are often spread across multiple departmental budgets in order to provide full coverage and are often overlooked when talking about legacy compared to SaaS applications.
Can this now be transferred to the production processes in paper manufacturing? And how should you proceed? To understand this, we first have to take a closer look at what are some of the areas where software generates the most overhead for organizations to manage over time. Since the answer varies across each manufacturing location and the heritage of how it matured over time, you can expect that there is homework to be done first. These questions are a good start for what to tackle up front when discussing business investment priorities and target locations for the investment into updating processes, methodologies and the technology that supports them:
- How many manufacturing locations have software over 5 years old? Of these, how many are managing critical tasks?
How much technical debt has been incurred over time for both homegrown and commercial software? What are the supporting technologies required for them to operate and are they also separately licensed?
- What kind of staffing is required at each site to simply keep the lights on for hardware and infrastructure management?
- What is the value of the current system and how long will it keep its value for the manufacturing site?
- Does it have a role specific for the site or does it influence the broader organization and how?
- What is the level of effort required to report across multiple locations and to maintain these reports over time?
- How well coordinated are planning, logistics, operations, quality, and maintenance teams?
With these answers fresh in your mind there is likely some growing interest in how exactly this would work to fit for the paper industry and your needs.
Success Stories of Cloud in Manufacturing Plants
While this may still sound like a dream of the future for the paper industry, there are already experiences with cloud-based MES solutions in other industries, for example in the automotive industry. This company, Smart Press Shop, used a cloud-first development strategy for building core ERP and manufacturing execution systems (MES) to digitalize production from start to finish – and run entirely in the cloud using 100% green energy.
It makes sense to take a closer look at the details to be able to better assess further developments for the paper industry, especially with regard to issues such as feasibility and reliability. What has become clear is that even for cloud-based systems, MES options for expansion and for customer-specific adaptations are absolutely necessary. Every company has its own individual manufacturing processes and precise ideas of how, for example, the user interfaces must be designed to provide optimum support for the workers. Accordingly, the solutions must be flexible and adaptable through the use of APIs and extendable by additional industry- und customer-specific functionalities.
The same applies to integration with existing automation systems and databases such as historical process and energy data. Many companies have been able to derive great benefits directly from this. For example Arpa, a manufacturer of surface materials, wanted to lower resource consumption and waste while keeping quality and time to market high by optimizing the product’s complex production process. They designed and built a new factory from scratch built on SAP software. SAP Manufacturing applications automate production and operations are optimized through the collection and analysis of data from each system, subsystem, and sensor. AI and machine learning technologies help Arpa constantly improve performance and sustainability. Smart, automated fine-tuning of the manufacturing process reduces energy and water use by 80% while machine learning algorithms slash scrap waste to near zero. Productivity increased 6-fold with a 24x7 production cycle powered by autonomous, laser-guided vehicles (LGVs). And €750k in production costs savings were realized during the factory’s first year of operation.
The analysis capabilities and the application of intelligent technologies such as Big-data, ML/AI and predictive analytics in the MES and ERP systems are clearly superior to those at the operational level in SCADA and automation systems. In the combination of operational and business data, there are completely new ways to find the parameters that influence product quality or optimize energy consumption.
Another important point is that although cloud-based solutions have developed rapidly in terms of reliability and security, there are often still good reasons for local implementation at individual sites. Among other things, the Internet connection in remote locations, high data rates and security can play a role here. Accordingly, a hybrid approach is required here, which, where necessary, also allows an edge, i.e. local, implementation in addition to the purely cloud-based setup. However, all of this should take place within a uniform architecture to enable uniform setup and evaluation.
For more information on SAP Digital Manufacturing Cloud go here.
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