Manufacturing 4.0 Made Possible

COVID-19 and the workforce shortage combined with increased personalization and production demands from customers have created a complex and challenging manufacturing landscape. The key to mitigating challenges and navigating today's manufacturing complexities is ensuring you can consolidate and optimize processes, contextualize all your data, and make Industry 4.0 work for your organization.

Aegis' CEO and co-founder Jason Spera recently sat down with SME Media to discuss making smart Manufacturing 4.0 technologies a reality. What is manufacturing 4.0? This blog will look at some of Jason's insights and experiences with implementing an IIoT-enabled Manufacturing Execution System (MES) in challenging manufacturing environments. Specifically, we'll detail the workforce shortage and post-COVID world challenges and explore how system consolidation, data contextualization, and artificial intelligence (AI) can help transform factories into Industry 4.0-enabled powerhouses.

Working Through the Post-COVID Workforce Shortage & Supply Chain Issues

There is a significant labor shortage affecting nearly all industries today, including manufacturing. Traditionally, younger engineers might view manufacturing as a less-appealing career choice—but that's rapidly changing because of the advancement of automation and digitalization. Technology is now playing an integral role in attracting new talent to manufacturing.

The industry is using manufacturing 4.0 technologies to solve today's problems and one driving force for change is the augmentation of unskilled labor. Upskilling and advanced smart Manufacturing 4.0 readiness can help to mitigate the workforce shortages. Digitalization helps empower lesser-skilled workers by making production easier for them. One of the key factors attributing to this empowerment is the user interface design of the solution. The visual appearance of the interface and ease of use are essential to accelerating user adoption. By leveraging a zero-code interface design capability, manufacturers have the power to make the user experience as simple or complex as needed without needing to know anything about how to write software.

The manufacturing world has never seen supply chain issues like we are seeing during this post-COVID timeframe. Manufacturers have come to rely on MES solutions like Aegis' FactoryLogix to maintain operations throughout periods of great demand. Furthermore, Aegis has helped industrial manufacturers switch their production models over to making medical devices during the pandemic, allowing customers to shift their production type and vertical overnight.

Enabling System Consolidation Across Factories

Multisite manufacturers are rightly concerned about different manufacturing systems and processes taking place across their various factories. Some say that different locations manufacturing different products also require different systems. But this approach leaves the manufacturer leveraging various solutions from assorted vendors, making it challenging to manage and share best practices across sites and product areas.

This issue can be solved with system consolidation through one singular, modular MES. While every area of manufacturing software requires a significant investment, there is a big difference between solving a problem and simply throwing money at it. Manufacturers may think that if they're a multisite organization, there's no way a single system can effectively handle their programs across sites. But a proper platform can.

The foundation of an effective multisite platform is the IIoT engine. It is important to note that a "platform" that consists of multiple tools or systems is not a platform. Instead, a true platform approach will provide customers with a vast breadth of capabilities in one modular system that meets individual site requirements while providing cross-site visibility.

Tackling the Data Dilemma

Another top challenge for manufacturing organizations today is data insight. With the increasing volumes of IIoT data being gathered from machines, systems, and people, manufacturers frequently struggle to manage and leverage this information to enable smart decision-making properly.

Manufacturers can tackle this data dilemma by implementing a solution that provides contextualized data that is accessible and useful. Despite all the functionality of an MES, it is still of limited usefulness if you cannot retrieve data in a meaningful way. The ultimate value of a powerful MES is in the analytics.

The manufacturing industry has progressed through a data journey hype cycle that can be summarized in three steps:

• First, everyone focused on simply trying to connect to all their machines to extract the data.
• Then the focus shifted to "big data" and the obsession to fill these data lakes with as much data as possible.
• Now there is the premise that we can simply leverage Artificial Intelligence (AI) to somehow magically create meaningful information context from all of these data lakes.

By populating data into a meaningful contextualized ontology, a data schema that brings meaning to the data, making analytics meaningful and straightforward. From there, manufacturers can achieve ultimate data flexibility. For example, it's an easy process if a manufacturing executive asks for another way to cut the data.
Leveraging AI & the Manufacturing 4.0 Definition

Manufacturing 4.0 (or Industry 4.0) is realistic for manufacturers of any size, but the "Industry 4.0" definition and smart manufacturing 4.0 meaning varies by organization. While Industry 4.0 is now truly in the eye of the beholder, it can still be succinctly defined as achieving real-time adaptability in manufacturing. This is when an organization can adapt to any kind of load, capacity conditions, or even single-piece flow without needing additional human labor or heavily customized software. Industry 4.0 is the benefit of highly adaptable automatic production.

AI can help manufacturers harness data to meet demand and enable smart manufacturing in Industry 4.0. AI can now give recommendations on improvements while also accounting for personalized production demands. One of the greatest values of AI is its skill in looking at data sets for patterns. While humans are limited in their ability to deal with data, AI can analyze more information than humans care to digest. AI needs to be applied to data, so it reaches out proactively to workers with actionable recommendations. This is an exciting frontier for the future—leveraging data in the way that only machines can, then getting it to the people who can translate it into action.

Choose a System that Empowers Your Factory's Lean Manufacturing 4.0 Efforts

Aegis has been able to help many manufacturers embark on the mission-critical selection of a digitalization system for their busy factories. The best way to mitigate risk and maximize success in finding the right solution, however, is to not fall into the trap of missing the forest for the trees. Instead, manufacturing leaders should keep their eye on what the benefits of Industry 4.0 are for their specific business and ensure that their solution aligns with those benefits. The best projects, according to Jason, are where leaders keep an eye on the guiding light of what they desire to achieve in their end state.

To listen to Jason's interview, visit Manufacturing 4.0 Made Possible.