Industry of the future: Discover the key pillars- ST-One

Pillars of the Future of Industry

In face of new demands and new possibilities, what can be expected from manufacturing industries in the coming decades? We’ll show you.

The tech industry expands the barrier of possible new creations every day, and within these possibilities, it is necessary to establish what will be the improvements that really are relevant for the future. From error prevention to estimation of results, these are the four pillars of the industry’s future.

ESG

ESG (Environmental, Social and Governance) are reports carried out by industries in order to show some of their sustainable practices and attract investors. The topics covered are related to the environment, social and governance issues, and some relevant points to be addressed are the following:

Environmental: the companies’ actions to combat environmental damage. Within the creation of ESG, it is necessary to document the measures taken in relation to the company’s environmental impact.
Social: how relationships develop within the company to its employees and customers. The measures are taken to make the workspaces suitable for everyone involved.
Governance: regulations above the representatives of the companies, the means of mutual supervision for internal and external affairs of the company.

The creation of ESG aimed to ask industries about their non-profit contributions. The demand has become increasingly growing to the point of generating discussions above the creation of standardized ESG reports by industries.

Machine Performance

Within large manufacturing industries, the full functionality of all its parts is essential for a positive outcome. With the high demand and attention required, this can be hard work with only little reward.

The digitization of performance data is the way several companies have found to have greater control of their industries. Through the monitoring of machinery, it is possible to make adjustments to more specific and functional methods. In addition, the prevention of any errors and problems can be carried out quickly, avoiding material and time losses.

Monitoring the performance of machines is one of the steps to improve performance, but it is followed by other strategies, as seen below.

Predictive Maintenance

Predictive maintenance is a data integration resource that predicts the need for maintenance, to have control over the machine and improve its useful life. This type of maintenance differs from preventive maintenance in that it uses real-time data, while the other is based on history and statistics.

As previously mentioned, predictive maintenance is based on real-time data, obtained from overview monitoring. This happens continuously during the functioning of the machines, and can be carried out in periodic, remote or online organizations.

Before using this resource, it is necessary to make some observations about the demands of the manufacturing industry – such as machine evaluations, system evaluations, integration, etc. – and study the results of the implementation, as well as work and study this data.

Some of the attributions on predictive maintenance are:

Minimization of time lost to unexpected problems;
Minimization of time for repair;
Maximization of machine safety and reliability;

Product Quality

“Is the totality of the requirements and characteristics of a product or service that establish its ability to meet certain needs”.

– American Society for Quality (ASQ)

With just these four changes, in addition to a noticeable improvement in overall productivity, the final results are improved. Still, there are points to be highlighted focusing on the quality of the product.

Product quality is determined by many factors. The evaluation criteria must be related to the object of study, but, in short, there are some points to be taken into account in all cases.

Physical integrity is the starting point for any evaluation. The product must be in full condition of usefulness. In a situation where the product is not approved in this aspect, other criteria begin to be impaired, such as performance. From an affected performance, the consumer’s expectation is broken, and the reliability of the product is damaged, resulting in a consistency problem.

Within the new reality of the industry and its relationship with Big Data, product quality management is intrinsically linked to the data acquired. It is through the implementation of better and smarter strategies that the production and quality of products is improved.

The four pillars of development for industries’ future open up many opportunities for system improvement and improvements in overall and net yield. Even so, there are demands concerning all changes and these must be studied and applied within the boundaries of the industry.