Data Analytics and how to make the best decisions for your plant
by Lantek
Digital Transformation
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Data on operations, processes, logistics, personal data, financial data... Data, data and more data. Too much data. So much data, in terms of quantity and variety, that it can be overwhelming. What is the best way to collect and organize them so that they make sense? To know what to do with them, so that they boost the productivity and efficiency of the plant?
Alberto Martínez, CEO of Lantek
In addition to the other improvements proposed by Industry 4.0, Data Analytics is essential to exploiting the value of the information. Now, when I speak of value, and pardon the repetition, it is, in fact, derived from the data itself. According to a report by Forbes Insights and EY, based on the opinion of 1,500 executives from large companies worldwide, 66% of companies with a well-defined advanced analytical strategy improve their operating margins and profits by more than 15%. It is clear, then, that on the road to digitization, a significant growth opportunity is provided by the effective analysis of the information that we generate in our companies.
The challenge is, therefore, to be able to know how to structure all of this information so as to optimize processes, identify areas for operational improvement, and strengthen the relationship with customers; in short, to enhance business growth. Aided by specific software and other technological tools, data analysts extract, select, process, analyze and organize data in order to establish patterns, trends, partnerships, and follow-ups that help us to be able to make the best decisions possible at all times, using the most disruptive business model possible, in terms of production schedules, maintenance, processes, inventory management... all of this in real time, automatically, which in turn results in greater cost reduction.
Now, if that described above were not enough in itself, Data Analytics facilitates decisions made in advance. Said in plain English, it will no longer be necessary to have to send e-mails to the different departments so that they communicate some type of data to us that, if not located, would take a great deal of time to find. With digitization, we are able to be aware, for example, before the assembly has concluded, of whether the result is to be optimal, we can predict scenarios that could delay production and repair them, and even the machines themselves are capable of resolving potential problems.
Conclusion: data analysis helps to avoid missing any details involved with the production process.
How do we translate what the data tells us? As a starting point, let us use the analysis that they perform in the technological consultancy firm Principa, using the four types of Data Analytics:
What is happening? This is the most basic of interpretations. We visualize all of the data in order to carry out a descriptive analysis of the business, its products, and its customers.
Why is it happening? A second step of descriptive data analysis is to apply diagnostic tools to determine whether there are potential problems, so that they may be resolved.
What is most likely to happen? Here, the possibilities of Data Analytics in terms of prediction are significant. The probability of occurrence of some incidence, which we can in turn resolve before it occurs. This ability to predict allows for better decisions to be made.
What do I need to do? The last step is from the prescriptive model, in which an analysis is performed to determine what has happened, why it has happened, and what could happen, in order to make decisions together.
However, Data Analytics is merely one of the cornerstones of digital transformation. If we add the possibility of learning from the data (Machine Learning) and creation of an Artificial Intelligence, as well as to connect our plant with sensors (Internet of Things), or upload all our Big Data to the Cloud, then we will have indeed reached the apex of Industry 4.0.
Regardless of the degree of digitization of a plant, it is essential to be familiar with each of its processes by using data, and thus gain a competitive advantage, which increases profitability and helps us to generate disruptive business models. For those who are not able to take adopt to digital transformation on their own, this new Revolution favors collaborative environments. There is no excuse for us all not to transform and to become more competitive. Choose the leading partner in your industry.
경쟁이 치열한 VUCA(Volatility: 휘발성, Uncertainty: 불확실성, Complexity: 복잡성 및 Ambiguity: 모호성)의 현재 환경에 직면하여 산업 설비의 디지털화는 시장의 요구사항에 빠르게 적응하기 위한 필수적인 차별 가치입니다. 플랜트 생산을 최적화하고 기록적인 시간 내에 민첩하고 개인화된 제조를 요구하는 새로운 소비 습관에 대응하기 위해서는 그것이 필수입니다.
최적의 결과를 내는 디지털 팩토리를 달성하는 데 있어 인더스트리 4.0으로 인해 우리 앞에 놓인 난제를 해결하려면 변화의 흐름에 잘 녹아들고 오류가 없는 방식으로 이런 난제를 극복하는 데 도움이 될 솔루션이 필요합니다. 이런 난제를 잘 인식하고 있는 Lantek은 플랜트 데이터를 실시간으로 수집해 분석하는 동시에, 기업의 경쟁력 강화를 목표로 의사결정을 개선할 수 있게 해주는 솔루션을 개발했습니다. Lantek Analytics와 Lantek MES를 통해 전통적인 Manufacturing Execution System과 데이터 분석의 힘을 합치면 첨단 및 지능형 제조를 위한 기초 역할을 합니다.