Industry 4.0 - How to Ensure Successful Implementation

There is no doubt that the world is becoming increasingly digital. Today, 127 new devices are connected to the internet every second, people check their mobile phones around 150 times daily and the processing power of computers doubles every 18 months. As far as the manufacturing industry is concerned, the tools associated with Industry 4.0 have been part of organisations' strategic plans for several years now. However, 7 out of 10 digital transformations fail.

Why are digital transformations failing?

There are several reasons that lead to the failure of a digital transformation project. At an initial stage, the lack of a complete diagnosis of critical points and design of a clear digital strategy can lead to the implementation of digital solutions in low priority areas and activities with little return on investment. Moving to a global rollout without first conducting a successful pilot, and defining a phased deployment plan can be another reason that leads to a never-ending rollout.

Furthermore, moving towards implementing digital solutions without understanding the business can also result in automating waste rather than addressing the root causes of problems and simplifying processes. Finally, the disregard for company culture and for training people in the new tools contributes to the lack of motivation in using the new digital tools.

What is Industry 4.0?

Also referred to as the fourth Industrial Revolution, its aim is to improve process efficiency and productivity through the implementation of three major complementary approaches: automation, digital information flow and advanced analytics.

Automation refers to the application of computerised or mechanical techniques with the aim of reducing the use of labour in any process. This is done using industrial manufacturing robots, collaborative robots, automatic guided vehicles (AGV) and autonomous mobile robots (AMR), automated warehouses and various additive manufacturing techniques (example: 3D printing).

The Karakuris systems are also considered automation systems although they are technologically simpler solutions that use gravity to mechanise physical tasks. Some examples of automation in semi-automatic production lines are automatic palletising or moving products on conveyors.

The second critical axis for a digitalisation process is related to the information flow. Automating the data collection on processes, equipment and manufacturing is key to ensuring a continuous flow of up-to-date information. In order to obtain this, it is necessary to install data collection sensors, to connect equipment (Internet of Things) and to use virtual/augmented reality.

The use of sensors at key points in the process enables the most important information to be transmitted to the control rooms, such as temperature or speed, which is later used for decision-making. Augmented reality, on the other hand, can serve to carry out maintenance tasks remotely. In this case, the operator performing the tasks on site wears virtual reality glasses that allow him to communicate with a specialist technician who is in another location, showing him first-hand what’s being done and receiving instructions by voice or images from the remote specialist.

As for advanced analytics, it handles and analyses information from the various processes in a much faster way and proposes solutions for well-founded decision making. This is done using tools such as data mining, business intelligence reporting, digital twin and artificial intelligence.

An example of the application of these tools can be, based on the data collected by sensors, to make wear and tear forecasts of the parts of a piece of equipment, or correlations between the variations of the different process parameters and the final result in the produced product.

Although the process of collecting, processing, and analysing data can also be done manually, through observations and time surveys, the digitalisation of this process brings greater reliability and speed, allowing decisions to be made more quickly and assertively.

How to succeed in implementing Industry 4.0

Upon reviewing the list of technologies listed above, it quickly becomes evident that they support the business. As such, and to exploit their full potential, it is necessary to start with a digital maturity diagnostic to understand what the current situation is. This diagnostic assesses the maturity of the organisation according to several aspects, namely digital and data governance, cybersecurity, employees' digital skills, agile implementation, automation, digital information flow and advanced analytics.

Once the digital maturity has been diagnosed, the identified deviations compared to industry standards should be analysed and the digital solutions applicable to the pain points and opportunities detected should be understood. At this stage, it is crucial to compare the ROI between each of the identified solutions.

The next step is to implement in a pilot where processes should first be reviewed before any digitalisation. This review includes the re-engineering of critical processes which ensures that wasteful automation is avoided. This pilot phase serves to validate the designed solution concept and confirm the expected ROI. It is an essential step for the success of the company's global transformation.

Once the successful implementation of the pilot has been confirmed, a multi-stage roll-out should be initiated. Firstly, at the level of the pilot area, i.e., a department or a site - and only then to extend the process globally to the whole organisation.

Management and technology must work together to achieve a successful digital transformation, ensuring a focus on people and processes. Throughout implementation it is essential to ensure that employees are trained in the new tools, that leadership is involved in the strategic incorporation of this initiative, and that the ROI is evaluated in each new area where the solution is implemented.

#digitaltransformation #assemblymanufacturing #processmanufacturing #operations

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