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.
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.
모든 것이 점점 긴밀히 연결되고 데이터 교환을 통해 공정에 필요한 데이터가 공급되는 환경에서는 공장에 배치되는 시스템의 오케스트레이션이 그 어느 때보다도 중요해지고 있습니다. 이는 회사 내에서 생산 공정을 올바로 구성, 정렬, 조정할 필요성, 즉 인력, 기계, 소프트웨어와 같은 모든 요소가 생산 공정의 적절한 곳에 참가하고 기여하도록 작업을 균형 있게 분배하는 것을 가리킵니다.
무언가를 더 이상 사내에 보관하지 못하면 통제력을 상실했다는 기분 때문에 혼란스러울 수밖에 없습니다. 직접 보고, 만지고, 다룰 수도 없으며 지도에서도 찾을 수 없어 많은 사람들이 쉽게 이해하지 못하는 공간인 클라우드로 중요한 데이터를 마이그레이션하는 경우에 그러한 상실감은 더욱 큽니다. 그리고 누구나 알고 있듯이, 사람은 무언가를 이해하지 못할 때 그것을 무시하고 마치 존재하지 않는 것처럼 행동하는 경향이 있습니다. 그러나 이 인더스트리 4.0 기술 구현 수단은 실제입니다.