The industrial sector has always worked to reduce energy costs in production processes. At times when the price of energy is very high, this is even more important and can often lead to factory shutdowns while waiting for prices to fall.
What are the implications of technological developments for workers and what should the relationship between the two sides be like? Focus on the human factor in the current and future industrial sector.
Industry 4.0 is presented as the promised land of the 21st century in which the vast information available and the interconnection between a multitude of elements allow more effective and efficient operation. But this great data collection machine must serve some purpose.
Efficiency is like magic. It allows you to achieve the same results with fewer resources and is greatly appreciated in optimizing energy expenditure.
Be it a house, a car or a nuclear power plant, maintenance is a key consideration when building or acquiring a new asset. This post introduces some concepts related to aircraft maintenance.
One of the most important challenges that Energy Trading departments face is how to deal with uncertainty regarding purchase and sale decisions. In this post we will explain, with a very simple example, what it entails to optimize these decisions in uncertain volatile markets, where predictions are not sufficiently reliable.
Although the word "trading" is usually associated with the stock market, in which Prescriptive Analytics is used extensively to optimize purchases and sales of securities such as stocks or bonds, it also exists in other markets, including energy.
Prescriptive analytics was missing in this industry's transition to the 4.0 paradigm, in particular in the areas of production planning and scheduling.
Very few leaders in the business world discuss the need to exploit their existing data to make decisions and incorporate advanced analytics into their processes.
How algorithms rule the world The NSA revelations highlight the role sophisticated algorithms play in sifting through masses of data. But more surprising is their widespread use in our everyday…