How to Prepare Your Path to the Autonomous Factory

The Autonomous Factory: this term has gained popularity in the context of Industry 4.0. In this article, we will discuss what an autonomous factory means and how manufacturers with multiple plants across the globe can move towards this coveted autonomous manufacturing infrastructure in their value chains.

What is an Autonomous Plant?

Let’s start with a definition: what is an autonomous plant?  Simply, it is a manufacturing facility which is able to learn what is happening within and beyond the manufacturing process, adapt to changes encountered while the process is being executed in real time and take informed decisions on its own, to implement measures which ensure there are no losses due to contingent changes encountered. This factory is the ideal outcome of unleashing Industry 4.0 in existing manufacturing plants; however, the path towards this is complex and needs careful planning which we will discuss.    

Autonomy in operations is the ability of a manufacturing process to act decisively to prevent losses without human intervention. The process which is truly autonomous self-optimizes and auto-adjusts iteratively to maintain desired process KPIs and ensures there are no losses, no delays and no disruptions. Such a plant is constantly communicating with process equipment, material in movement across the shop floor, measuring all process parameters. It is also connected to and relaying information to and from enterprise level applications like ERP, allowing the production to run uninterrupted.

The human role from a process execution perspective in such plants is to monitor overall execution and perform/apply/adjust as advised by the intelligent applications operating the plant and orchestrating the process, which allows the ‘human’ component of the process to concentrate on his/her core activities.

A fully autonomous plant is at the peak of digitization, where all modern technologies like AR, VR, Robotics and Machine Learning/AI, among others are fully deployed. The goal in a fully digitized and autonomous manufacturing operations infrastructure is to have all plants in the group/company at a similar level of digitization, so that the benefits of Industry 4.0 can be realized uniformly across the group and implementation efficiencies can be realized through mutually shared and gained knowledge and experience.

How to Approach

To achieve such level of autonomy is a complex endeavor, and one which may result in complete or partial failure if not approached properly. The important thing to understand here is that while all of the technology needed to achieve an autonomous plant exists today, the way in which this project is approached and technology partners engaged to achieve said digital transformation are critical in the project’s eventual success or failure.

The pertinent questions then become, how does one approach the whole autonomous factory project? What are the crucial factors which determine the success of such a project? What is the key ingredient in ensuring a successful transformation from status quo to a fully digital autonomous factory set up?

Let’s try and answer these questions as we move along.

First and foremost, the top management of the company must realize the need to digitally transform. The best way to do so is to understand what this transformation exercise will achieve. For most top executives around the world and across all types of businesses, their primary goals are to reduce cost of operations and increase profitability, among other corporate goals; the Industrial Revolutions, all of them, aimed at these exact objectives, which were to allow for higher quality goods to be produced at lower costs, thereby enabling higher profitability. Industry 4.0 follows this strategy, offering the ability to produce higher quality goods at lower costs, in reduced timeframes, with higher precision, the result being increased profits.

In a factory which already has Industry 3.0 technology and has deployed the full array of lean and associated TPS methodologies, there might still be massive delays in the case of an unplanned event or disruption. There may be delays in getting insight into that an event has occurred, and there may be a delay in analyzing where the event occurred, how it occurred and what has now been damaged or lost because of it. There may be other delays in deciding what to do and finally a delay in actually getting done what needs to be done. All of these delays result in  money being lost due to the wasted time, and the time that is wasted is not necessarily due to lack of data, rather the ability to harness that data in real-time, analyze it and propose swift and decisive actions.

This is where Industry 4.0 kicks in; in an autonomous plant, an untoward event which disrupts operation might not even occur, as the plant is already capable of predicting such an occurrence and adapting processes in order to ensure no disruption or downtime happens. But this is an ideal scenario; even when the plant is unable to stop a disruptive event from happening or negatively impacting the operation, an Industry 4.0-enabled plant, which is to some degree autonomous and likely has a modern MES orchestrating the process, would still be able to detect the issue, analyze what went wrong and report the information to process owners. The MES may suggest both corrective and preventive action, which would then allow for actions to be taken immediately, resulting in far lower wasted time and reduced losses.

Time saved is money saved, and that’s what the digital transformation from an existing set-up to an Industry 4.0 set-up achieves, among other benefits. This is why a digital transformation is needed; leaders who do not act now will be responsible as their companies are left behind and eventually lose out their competitive edge to other companies which saw the need, made the moves and are now partially or fully digitized.

How to Approach Autonomy

So the need for digital transformation and creating an autonomous plant infrastructure is understood, but how is it to be approached? Well, it is imperative for the top management to understand that the data and technology which is needed to achieve an autonomous factory already exists today. The key is for the management to see the benefits and then get the team across plants to support the challenges of digital transformation. Once the leaders and process owners are on board with the need to pursue the Industry 4.0 project, the subsequent tasks will be easier if well planned from the start.

True understanding of the current process and state of plants across the value chain from a technology and digital perspective are next; in reality, even the most modern plants still collect data manually and depend on operators to then share the data, either on paper or through reports, which are always after the fact.

Drawing a clear picture of the technology landscape will enable the formation of a tangible vision of what needs to change and where the plants need to be in a period of the next three to four years. To establish this vision and conduct this analysis, participation of shop-floor personnel from various plants, supplemented with external consultants, might be the most prudent approach.

Once it is understood what the status quo is and what the future needs to be, the project can then be formally kicked off. Recognizing common capabilities, both digital and operational, and the shared areas of improvement across all of the plants should be a key deliverable. Once the internal analysis is done and the baseline is established, the roadmap of future operations can be built, which when implemented by the project team will deliver the desired level of automation and other improvements, which should be uniform across all plants or can be replicated across plants, depending on the deployment strategy followed. 

The path to achieving an autonomous plant infrastructure becomes:

a) The establishment of a common operating vision for all plants.

b) The determination of, and agreement on, the current and common digital capabilities across plants.

c) Drawing of a clear, autonomous roadmap, envisioning the journey of the plants through the transformation.

d) Establishing a best practice sharing and baseline deployment process, to be reviewed and enhanced as the project moves along.

e) The deployment of requisite IT applications, based on agreed and established technical standards and integration protocols. 

f) Development and deployment of a common implementation model and operating model to harness implementation efficiencies and leverage common organizational models. 

Results

The goal to be achieved by following this path is not just limited to achieving a digitally enabled value chain and autonomous manufacturing plants. Rather, it is to ascertain that continuous improvement and productivity gains are pursued across all plants, at a higher speed, with lower costs. The end result is the flexibility and robust supply chain infrastructure which truly reflects the difference between an Industry 4.0-enabled supply chain and an Industry 3.0 supply chain.

It is critical to point out at this stage that Industry 4.0 is all about building an integrated technology infrastructure, with manufacturing operations systems at its core and IT applications like the MES as the backbone of achieving this digital transformation.

The right MES partner and application can be the very factor which decides how well your digital transformation eventually pans out, so during the time of analyzing status quo, seek expert help in understanding what sort of MES would be best for your plants.

This answers the final of the three questions we posed earlier pertaining to the key ingredient of a digital transformation. The MES application is the most critical piece in the pursuit of the autonomous factory; it is the application which connects the shop floor to the top floor, provides real-time data from the process in the form of information, which can either lead to action which is automated and predicted by the same application or be acted upon by a process participant; this depends on the level of autonomy achieved and desired. So choose the wrong MES at your own peril; choose the right one and you are already ahead of competition in this journey of digital transformation and autonomous manufacturing plants! To understand more about the Path to an Autonomous Factory, please watch our webinar on-demand by Medtronic’s Paul Straeten, Head of Manufacturing Information Technology.

Jeff Richardson
JeffRichardson@criticalmanufacturing.com

Industry Solution Director at Critical Manufacturing

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