The Evolution of Industry 4.0

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First and foremost, what is evaluation criteria? Evaluation criteria are basically from the joined terms of evaluation and criteria. Evaluation, by definition, is a systematic determination of a subject’s merit, worth and significance, using facts governed by a set of standards. Criteria is a principal or standard by which something may be judged upon or decided.
Therefore, evaluation criteria are standard measures used to evaluate the extent to which alternative solutions, ideas, or policies are able to meet expectations or objectives through a direct contrast of their strengths, weaknesses, and adaptability.
Industry 4.0 is what defines the current state of industrial significance. It is what is known as the Fourth Industrial Revolution which will transform the manufacturing and production industry by introducing advanced technology such as the Internet of Things (IoT), information assimilation, cloud computing, Artificial Intelligence, among many others.

Industry 4.0 is mainly characterized by the coming together of two principals that had never been done before. The bridging together of Information Technology (IT) and Operational Technology (OT), which is essentially bringing the digital and physical production complex into life
Industry 4.0 is not all about factories and manufacturing anymore. A lot of this has to do with the fact that everything has become digitized and as we know it, times have changed and consequently, strategies, ideas, and solutions to tackle situations are bound to change too. Technology has become a major influencer of the current industrial phase and now it seems to have taken over all the functionalities and systems involved in manufacturing and production. The digitalization of all elements of production is essential for a new era in industrialization.
Evaluation criteria have always been a key stepping stone even to an evolution of the industry as it is now. Through ideas and sorting out solutions, it has led to the innovation and creation of new systems to solve problems that were there during Industry 3.0.
The criteria used in evaluation would have to do with the considerations of 4 factors. They include:

• Relevance
• Efficiency
• Effectiveness
• Impacts
• Sustainability

Relevance is a measure of the extent to which development involvement and activities meet the solution of the problem that is at hand. With the various systems and technological parities found in this industrial era, solutions and actions can be found within a matter of short time.
With interconnectivity, globalization and the Internet of Things, it is pretty much easier to identify a solution to a task at hand. With other industrial eras, fixing something up had to mean you consult the help from other specialists who would then be available for productivity.
With technology today, the situation is different as there is only one way to solve any problem, the internet. You can access relevant information worldwide and even sort the services of the best specialist within a whisker of time. A process which could have taken longer to implement without this sort of help.

Efficiency is a measure of the process involved between productivity or outputs, i.e. the result or services of a product, and inputs, i.e. the resources that were used.
In Industry 4.0, a lot has changed in the face of production. A lot of human resources used to be depended on to produce various goods and services. But due to the error of men, such as fatigue, illnesses, boredom and other examples of inefficiency and inconsistency, professional help was implemented through the use of AI or otherwise known as Artificial Intelligence.
By definition, Artificial intelligence is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. The use of machines was readily welcomed in this industrial era as it bore more merits than demerits. For one, for a programmed machine to make a mistake, it would be next to zero, if not negligible. The output of machines is more efficient to that of humans as a lot of factors consider machines as the best to work with.
Another reason for implementing AI is that industries sort to figure out ways to reduce cost and at the same time fasten productivity. Humans were considered rather slow in nature and if more would be employed to help out, it would mean that they had to sacrifice more revenue for salary and remuneration purposes. Therefore the solution to implement a cyber-physical environment meant more productivity and connectivity that was far much better in the course.
With the implementation of human-robot cooperation and big data monitoring, production has almost been made to perfection. It will answer questions such as, “Where are the potential bottlenecks? And where is the greatest need for action?” This data is now easily accessible at all times.

In definition, effectiveness is the degree to which something is successful in producing the desired result; success.
In Industry 4.0, effectiveness can be measured by how a certain component applied to production can yield the desired results. Over the years, most of what was involved in the production was still missing that cutting-edge towards it. For example, in Industry 3.0, during the birth of electronic systems and automation such as CNC (Computer Numerical Control) machines, now in 4.0, the adoption of cyber-physical systems with innovations such as 3D printing in tool making, has brought a lot of what would be considered a remarkable innovation in human era.
The nature of manufacturing is changing as vaster customer-friendly designs are being produced to meet value for the customer and not only financial expectations.

The impact is a measure of all significant effects or results of an input. How Industry 4.0 has evolved evaluated criteria has affected even the impact it has had on the delivery of work and productivity.
With new tools, agility, scalability, and flexibility have since improved by a milestone. In the sense of leveraging new technology such as cloud software and Artificial Intelligence, the predictability of seasonal changes and demands has impacted the possibility of adjustments to avoid overproduction and underproduction in the market segment of the industry.

Sustainability is the measure of whether the benefits accrued to the industry have grown over time or have fluctuated with the demise of lack of proper usability of integrated systems.
With the current devices applicable as of now, a lot of effort has been put towards Research and Development which has brought about constant change in productivity and hence, sustainability of growth in the industrial sector.
The evaluation criteria used in research has changed as more investments put towards research will prove productive and feasible towards better innovative and ground-breaking tactics.

Marco Barchetti