Smart Factory as the Factory of the Future?

The technologies, potential use cases and characteristics underpinning the Factory of the Future, next advancement in operations.

Factory of the Future

The epicenter of innovation and improvement of manufacturing has always been the factory itself. To get the most out of the opportunities Industry 4.0 offers, organizations need to realize these technologies can improve processes throughout their operations.

In this article, we will first discuss several characteristics of the Factory of the Future.

Second, we will show that the benefits of these technologies and potential use cases manifest themselves throughout the entire value stream of the Factory of the Future. Finally, we will zoom in on several of these use case, such as the Digital Twin and Digital Shopfloor management.

Beyond the technology: which elements enable a Factory of the Future to get the most out of these use cases?

In another article, we discussed that Industry 4.0 is based on data and connectivity. Similarly, the basis for a Smart Factory (also called Factory of the Future) is the usage of data. ‘Smart’ in this context refers to being interconnected.

Using sensors and an adequate network, data is collected non-stop from all possible sources. This transparency allows for better and faster decision-making and increases productivity. The highest level of data use comes in the form of autonomous systems that can perform checks and make decisions independently from human intervention.

Combining this foundation of data usage with the tried and tested ideas of lean production results in Lean Digital. Thanks to the smart use of data, the lean methods increase even further in effectiveness. Instead of one-off exercises, the 24/7 recording of all processes allows for immediate responses to deviations in both directions.

We talked about data being the fundament and the core of Industry 4.0 and the Factory of the Future. The bedrock, however, to build this data-first approach on, is a scalable IT architecture. The amount of data generated on a continuous basis is enormous. Further, most if this data is still unstructured and complex.

Only a scalable IT architecture will allow you to get the most out of your data. This architecture needs to be rooted in a long-term IT strategy, which in itself, needs to be based on the overall vision and strategy of the organization.

Coming back to the physical world, the factory layout needs to be flexible enough to be adapted to all these new possibilities. It is one thing to quickly identify new actions to take. It is quite another to be able to quickly act accordingly.

Rigid layouts will prevent the right course of action and real value to be captured. This also includes the interfaces to other partners, which is where most often the difficulty lies in increasing flexibility.

Similar to the physical layout, the Smart Factory favors a modular and flexible approach to your equipment and teams. Concretely, a decentralized organization will enable quickest problem-solving and the most value added at every level.

The time and energy spent controlling is reduced to a minimum. Again, this is only possible when solutions such as RFID are coupled with sensors linked to all equipment. Such a set-up will truly allow for autonomous, decentralized decision-making in the Factory of the Future.

Getting your people on board with all of these new changes is one of the key differentiators to make your journey a success. Leadership and qualification are therefore critical.

Many functions will change, new roles will be added, skills and competences need to be learned. As is natural for humans, fear and resistance will rise of they are not pro-actively managed. In the Factory of the Future, your managers and leaders need to play a pivotal role.

Finally, the last element of the Factory of the Future are the actual technologies and use cases throughout your operations. Advanced Manufacturing is a broad term for all the different technologies in manufacturing and operations, relieving operators from physical tasks. Typical examples include AGVs (Automatic Guided Vehicles), cobots, augmented reality through Smart Glasses, …

All these elements need to be taken into account when assessing where your operations are now and what steps need to be taken to transform towards a Smart Factory. One final overarching theme should also be mentioned.

The sustainability dimension has rightly become key when designing the Factory of the Future. Environmental impacts such as water or energy consumption or wasteful emissions are to be reduced to the maximum. However, this also includes the avoidance of wasteful activities and disruptions in your operations. More and more, we see that sustainability and Industry 4.0 go hand in hand.

From planning to production and distribution: the Factory of the Future enables the transformation of all processes of the value chain through new technologies

It might be difficult to still see the big picture when talking about the Factory of the Future and all these new technologies. Where does each fit in our overall operations? Above figure gives a broad overview of the possible applications in every step of a typical process from sales order to actual delivery and related domains such as maintenance and quality.

A specific example of a new method under maintenance is predictive maintenance. This method uses both forecasting techniques and sensors. Combining these, guarantees that maintenance on equipment is done right when it is needed. In this way, unnecessary production stops are avoided and the necessary maintenance is still carried out.

Predictive maintenance methods can even go a step further. Specific critical elements can be monitored on a continuous basis, allowing even higher equipment availability and reducing costs even further, bringing your Factory of the Future to the next level of efficiency.

Below, we will elaborate on some of these use cases. First, we will zoom in on possibilities related to your warehouse operations. Second, we will explain the added value of transforming to digital shopfloor management. Third and finally, we will discuss a particularly powerful new technological advancement that is a building block in the Factory of the Future: the digital twin.

Warehouse 4.0

In combining the traditional lean methods so often used in Warehousing with Industry 4.0 technologies, new opportunities open up and warehouses become more efficient, more flexible, more connected and, as a result, ‘smarter’. The following topics are key to take your organization to the next level when it comes to Warehouse 4.0:

  • Dynamic localization: Localization technologies are evolving rapidly. Beacons, RFID and similar technologies will soon make it very easy to use methods such as in all warehouses. A geofence creates a virtual boundary, which will make the flow of goods within a warehouse very visual and even programmable. It is this same technology that will allow your smart lawnmower to know the perimeter of your lawn, without the need for a physical wire to indicate its boundaries.
  • Wearables: This is a very broad term incorporating any device or technology which can be worn. Headsets, Smart Glasses or Smart Watches will not only increase the ease of many tasks, such as order picking or even more complex tasks such as maintenance. Safety, ergonomics and communication will all improve drastically.


The core elements of any warehouse will be intralogistics: the set-up of all material and physical goods flows, including necessary support functions and processes.

Even today, the bulk of these intralogistic processes and flows are highly manual. Automation is still rare. A typical order-picker will spend most of his/her time walking or riding through the warehouse.

However, it does not have to be like this. The latest technological advancements of the Factory of the Future have profoundly altered the playing field. When evaluating how best to set-up your intralogistics, there are many possible solutions to take into account.

  • Autonomous transport robots (AGVs)
  • Smart Racks / Smart Shelfs,
  • Collaborative picking and handling robots (Cobots)
  • Combined assistance systems (example: Pick-by-Voice & Pick-by-Vision).

Where in the early days of these technologies the necessary initial investment was quite significant, this has changed a lot. Today, these technologies are modular and scalable. This even allows for a step-by-step or module-by-module roll-out. Therefore, the financial risk can be limited. Next to the cost side, the performance of these solutions has improved remarkably. Combining these two facts, leads us to a situation where it is now useful and possible to consider automation where this was not possible earlier.

In summary, the opportunities for automation and smart technologies in intralogistics are plenty. The biggest question to answer is which concrete use cases offer the biggest possible gain for your specific situation.

Digital Shopfloor Management

Digital shopfloor management’s main objective is to allow all processes on site to remain under control and, specifically, to do this by responding in real time to deviations from the norm. Centrally in digital shopfloor management is the visualization of KPI’s compared to its targets. Building on this, a clear incident and action management allows all involved people to respond when necessary.

Note, however, that digital shopfloor management is not about simply going from analog to digital by showing KPI’s on a central screen. The classic approaches and management methods used traditionally to manage the shopfloor should be built on.

What then, separates digital shopfloor management from these traditional approaches? In line with all other Industry 4.0 and Factory of the Future advancements, the focus is on integrated data from all relevant sources. This not only means previously discussed sensors and automated data gathering. It also encompasses gathering hard data from more soft sources such as actual behaviors, planned and unplanned maintenances, follow-up of actions, …

Putting all of this together, enables a true step-change in the speed in which deviations on OEE (Overall Equipment Effectiveness) are managed, bottlenecks are resolved and issues in production are tackled. Furthermore, the pro-active actions that are taken become that much more effective and on target, allowing for a general boost in productivity and decrease in costs related to all types of issues, from quality up until downtime.

Digital Product and Process Twins (Digital Twins)

Digital Twins are one of the more interesting possible technological use cases in the sphere of Industry 4.0 and the Internet of Things (IoT). In a nutshell, a Digital Twin is a model which is defined to represent a virtual copy (hence ‘twin’) of a real-life product, process or even situation. These dynamic models allow users to dynamically run different scenarios and, as such, predict risks, performance and critical points under changing circumstances.

Specifically for very expensive or critical decisions, Digital Twins are extremely valuable in aiding an organization in taking the right course of action. A Digital Product Twin can help in optimizing product set-up and maintenance of your most crucial and complex machines.

Digital Process Twins, on the other hand, allow you to perform an analysis and evaluation of an entire chain of different process steps or, even, of a complete network. As such, creating a Digital Twin of your supply or value chain is entirely possible. Involving your suppliers and customers creates a holistic picture and, similar to a Digital Product Twin, lets you run different scenarios with changing inputs. Hidden, yet critical bottlenecks can be identified. Resources and process steps can be optimized.

But how do you get started and define a Digital Twin? Let us take the example of a Digital Process Twin. First, the few process parameters that have an impact on overall performance of the process in scope are determined. The second step is data collection. This can be done by retrieving available data from the actual process. If this data proves insufficient, it may be necessary to collect data with sensors. All this data can be put together and analyzed in an overarching data model.

This forms the fundament of a model that includes the pre-determined process parameters, how these parameters interact with one another and what the crucial points are in the overall chain. As said, the Digital Process Twin will consequently allow you to test various possible scenarios and make real-time decisions with changing realities. Furthermore, other methods such as machine learning can be added to the Digital Process Twin, enabling even further automation.

OUR ROLE: guide companies in their journey towards the Factory of the Future

Should you have any questions after reading this article or if you are facing any of these issues yourself, you can certainly contact EFESO Consulting. You can also request a callback from our consultants.

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