How The Autonomous Manufacturing Revolution Relies on Successful Workflow Software

23 November 2022

[Image Credit: Sufyan via. Unsplash]

 

Fully autonomous manufacturing, the holy grail of almost every industry, is rapidly becoming an increasingly tangible possibility.

The manufacturing scene as it stands today is permeated by issues and shortcomings autonomous manufacturing promises to smooth out in one fell sweep.

Autonomous manufacturing, the phenomenon by which IoT features such as sensors and machine learning capacities are integrated into machines and grant them self-governance, offers to transform production into an entirely hands-free process. The consequences of this technology becoming widespread has the potential to be monumental.

The efficiency resulting from bypassing human intervention establishes unparalleled supply chain resilience, intelligent manufacturing modes and simplified production cycles freeing up space for effective contingency planning, both in the face of minor disruptions or wider crises.

There is a lot to look forward to where autonomous processes are concerned. However, it must be recognized that smart machinery cannot deliver these improvements alone. Simply replacing pre-existing technologies with autonomous alternatives can only alter business processes up to a certain point.

To truly reap the rewards of autonomous technology, investment in a singular advanced MES is essential.

In a 2020 publication of the journal Computers in Industry, the invaluable role played by MES in optimizing autonomous manufacturing processes is elucidated: “MESs should interconnect all components of cyber-physical systems in a seamless, secure, and trustworthy manner” (page 1). “Connection”, indeed, is a key component of MES’ invaluable functionality. Without a meeting point between different people, processes and technologies, it is nearly impossible for true ‘autonomy’ to be achieved.

The next five years are set to see autonomous manufacturing dominate industry manufacturing preference. According to Ericsson’s IndustryLab 2021 report, multiple industries are already seeing ICT-enabled tools take up significant space on factory floors. 25% of market respondents, for instance, indicated current usage of automated guided vehicles and autonomous mobile robots, expected to reach 67% in 2026. Strikingly, such data indicates that autonomous processes are likely to soon appear in the majority of manufacturing operations worldwide.

AMFG’s rapidly growing Manufacturing Execution System (MES) & workflow automation software for industrial 3D printing has recently secured breakthrough Venture Capital funding led by Intel Capital to drive the future of fully autonomous manufacturing. With this new funding, AMFG will continue to help companies scale and streamline their additive manufacturing processes worldwide – further proving AMFG’s pivotal centrality to the autonomous manufacturing revolution our world is launching into.

With more and more companies turning to autonomous technology, interest and investment in MES & workflow automation software are rising in positive correlation. In this article, we explain exactly why capable software is equally as integral to driving the autonomous manufacturing revolution as the machines are themselves.

Connectivity 

The creation of links between a company and additional or separate production units contributing to their processes is crucial to ensure seamless alignment between different operational loci.

The first hurdle to maximizing autonomous manufacturing’s benefits is establishing a coherent and connected system capable of facilitating unhindered contact between these divergent production spaces.

Smart machines conventionally employ sensors and IoT technology to share vital data regarding their performance. This information can then provide critical insights into the progression of manufacturing stages, notifying the completion of a certain site’s projects, flagging up machine malfunctions, and so on.

Removing the need to communicate this information manually is one of autonomous manufacturing’s greatest advantages. However, when it comes to broadcasting vast amounts of information from multiple sources in a coherent manner, manual management systems just don’t make the cut.

It is imperative that the information made available by autonomous machinery is accessible across a company’s operative branches. This is particularly pressing when facilities are scattered across the country or the globe, for example, making it challenging to coordinate autonomous operations efficiently.

The importance of such connectivity permeates multiple levels of the production system. This would include, for instance, the interconnectedness of individual machines across a factory, instigating essential communication between devices and enabling them to accommodate and adjust to one another with quick response times. More broadly, it can also involve establishing ties between upstream, downstream and third-party players in the manufacturing process, such as ensuring that raw material suppliers or external distributors are kept in the loop.

A successful workflow automation software should hold precisely this organizational capacity. Providing a single source of truth, separate components of widespread manufacturing proceedings are granted a unifying touchpoint.

It seems a simple thing, the provision of information to everyone for which it is relevant; however, the act of organizing these connections, and ensuring that immense quantities of data are kept up to date and channeled through an accessible GUI, is a hefty task. Adept software importantly offers to take on this weight.

As articulated by Manufacturing Business Technology, “at [Industry 4.0’s] very core is the vision of horizontally integrating production processes themselves so that they can be self-learning, self-healing, and agile”. In creating such a thoroughly connected network, higher quantities and velocities of data will be exchanged live, empowering machine learning to enhance performance to greater and greater heights.

Visibility and Transparency

 

Whilst the way in which companies stretch their operations across disparate operational sites is a key determiner of success, the layers within an organization’s internal structure must also be expanded and reinforced, allowing them to take ownership over their own processes. It is integral that autonomous production floors, for instance, are placed in close digital contact with other departments within the company, such as business strategists or sales representatives. A strong core should ideally be embedded vertically throughout the company’s hierarchy of roles, from the ‘bottom’ right to the ‘top’.

In an autonomous manufacturing context, it is essential for workers at every level to remain informed about project progression, ensuring that the actions taken at each stage slot into one another, working in collaboration rather than imposing bottlenecks. Reaction times are significantly quickened when transparency of information flow is available.

According to Professor Alexandra Bintrup from the University of Cambridge, “autonomous supply chains could be transformational for businesses, helping them to create better visibility and traceability”. Sensors integrated into autonomous supply chains certainly ensure that all processes are quickly and accurately logged. To develop on this, it is worth noting that software is majorly responsible for actually presenting this information clearly and coherently, rendering it useful to manufacturers themselves.

At the heart of IoT, upon which so much of autonomous manufacturing relies, is a network which places devices in meaningful communication with one another. Yet, the acquisition of a fully functioning ‘web’ of connected machines and operators is not an immediate given.

An autonomous manufacturing company may proudly gesture towards their extended range of cutting edge machinery, or their highly skilled mechanical engineers, as an indication of their expected success. Ultimately, though, it is software’s capacity to draw links between these nodes which can really activate these positive attributes’ full potential.

Data Collection & Analysis

 

 

 

Sensors play an enormous role in enabling the autonomy of smart devices. Ceaselessly collecting data of depth and breadth inaccessible to any man-made spreadsheet, manufacturing has subsequently witnessed immense sharpening of data collection capacities. Conveying invaluable information, from a product’s pending status or current status, to even predicting production outcomes, big data powerfully encapsulates the past, present and future of manufacturing processes, lending manufacturers the closest thing there is to business-oriented omniscience.

However, data collection can easily become superfluous if the information is not filtered or structured in a coherent way.

How do you pluck a meaningful figure from a roaring stream of digits? It can be difficult for businesses to pinpoint what information is relevant to their operations, and which can be safely discarded. Even preceding this, many often do not know what questions they specifically want a data set to answer in the first place, let alone how to put that ‘answer’ to use.

It has become common to describe big data as consisting of 5 ‘Vs’: volume, variety, velocity, value, and veracity. MES software can regulate and optimize each one of these properties.

Introducing a fixed framework through which to channel information is beneficial on multiple levels. The prodigious volume of data can be sorted into a manageable format, ensuring that the most essential information is made visible to decision-makers. Categorization breaks down statistical variety. The velocity of data flow can also be managed via such features as live updates and notification mechanisms.

By way of the overarching cohesiveness MES introduces, the veracity of the information can easily and regularly be reaffirmed. In turn, the value of the data to business operations and decisions going forward, sitting atop the hierarchy of ‘vs’, is brought within much closer reach.

Big data is deemed “one of the key technologies in artificial intelligence” in a 2022 publication of Engineering, Science and Technology journal. It involves “mining the hidden knowledge” integral for leaders to “make wise decisions in various complex manufacturing environments”. In order for these leaders to ensure that absolute certainty is backing their data-led decisions, a reliable workflow software is the tool to wield.

Flexibility to Grow

 

Stepping back and taking in the big picture, part of the excitement surrounding autonomous manufacturing as a prospect is its newness on the scene. Who knows where we might be five, ten or even fifty years from now?

As principles like Moore’s law demonstrate, fast paced refinement lies at the core of technological innovation. It must be assumed that the landscape will continue to shift. For this reason, it is crucial that workflow software systems can advance in conjunction with, and in enhancement of, the technologies which they manage.

One of the key distinctions between successful and unsuccessful workflow software, as a result, is adaptability. Whilst present-tense functionality is indubitably essential to ensuring positive outcomes, a future-conscious slant towards software development is equally as necessary.

Here’s the crux of the matter: when it comes to the autonomous manufacturing revolution, a successful software cannot exist in relative stasis. It must be eager to not only accommodate change, but to drive it.

Driving the movement towards autonomy in additive manufacturing, AMFG offers an end-to-end solution directed precisely towards streamlining and scaling AM operations in line with these principles.

Of its numerous modules, many work directly towards supporting success in the subsections this article has covered. Its software collects actionable data at every step of the production process, providing valuable insights to decision makers. These features, amidst many others, have firmly secured its position as a market-leading solution to scaling additive manufacturing operations globally.

Vitally, AMFG keeps a constant finger on the industrial pulse. Continuing to solidify their place as the go-to solution for 3D printing, they are surging their way towards making a revolutionary impact on the autonomous manufacturing sphere.

As autonomy permeates manufacturing with increasing velocity, AMFG will continue to fortify its influence in the field.

Conclusion

Autonomous manufacturing, at its core, offers production efficiency. The actual achievement of this goal, however, is more of a two step process – streamlining the manufacturing itself, and streamlining the processes surrounding it.

If you type ‘autonomy’ into Google, you will discover a two-pronged definition powered by Oxford Languages:

1. the right or condition of self-government.
2. […] the capacity of an agent to act in accordance with objective morality rather than under the influence of desires.

 

Here, ‘autonomy’ describes both independence itself, and the exertion of control over independence. In many ways, this duality of meaning encapsulates well the interdependent relationship between autonomous technology and the workflow software overseeing it. The existence of the latter is critical for managing the former.

Manufacturing is undergoing a period of immense change, with AMFG’s state-of-the-art MES & workflow software leading the charge.