Digitalisation and Big Data in Manufacturing Industry
2018-06-18
Artificial Intelligence, Smart Hospital, Cyber Security, Smart City, and Industry 4.0 were the hot topics at Techsummit 2018. Gradually, digitalisation applies to all areas of life and society, including public administration.
Estonian politician Kalle Palling attested that the improvement of public sector’s services occurred after relatively swift informatization, which transpired in the form of e-government.
Professionals in Artificial Intelligence cared to remind the visitors of the many advantages of human intelligence, which wouldn’t be soon outperformed by “thinking machines”. However, they did not hesitate to remark that the development of human brain capabilities need to be maintained.
The technologies of Augmented and Virtual Reality (AR and VR) are being progressively employed outside the entertainment industry, mostly for the training of new employees and re-training of staff or for the execution of maintenance tasks where the function of visualization enhances the effectiveness of repair intervention. Several voices at the gathering claimed that the future of production lies in additive manufacturing, in the form of 3D printing.
The topic of Big Data dominated discussions bordering on Industry 4.0 since Big Data is an integral part of the concept of Fourth Industrial Revolution (4IR) along Autonomous Robots, Digital Twin, Industrial Internet of Things (IIoT), Augmented and Virtual Reality, etc. Representatives of IT enterprises that collaborate with industrial enterprises, including ANASOFT, acknowledged the importance of data collection.
This undeniably crucial position also corroborates the current trend wherein most businesses are investing in data accumulation and analytics’ technologies, which is because decision-makers need to have the right information at their disposal and at the right time to make the right decisions.
The digital transformation of enterprise processes, also via modern industry solutions, such as Smart Industry Solution EMANS, enables effective data collection from shop floors and their subsequent processing for analysis, simulation, and forecasts. The accumulation of data is especially necessary for businesses that integrate Artificial Intelligence into their operations in the form of self-learning machines and auto-optimization operating production systems.
Among the most common use of data collection and visualization are labor monitoring, digital labor write-off, monitoring of manufacturing and transportation equipment and material, evaluation of Overall Labor Effectiveness (OLE), evaluation of Overall Equipment Effectiveness (OEE), material utilization effectiveness, generation of unique birth certificate for products, and transparency in manufacturing processes.
As a part of Smart Industry solutions, data is vital for the optimization of processes and augmentation of their effectiveness. For example, in the identification of micro-down-times or their causes, stages of poor quality in the manufacturing flow can be detected and removed by employing data collection and analysis.
Enterprises can harness the benefits of Big Data analysis in product customization (primarily to analyze consumer behavior) to secure quality of processes and products and manage the supply chain by way of predictive analytics.
Predictive analytics offers a wide range of application in manufacturing and logistics. Artificial neural networks process nebulous volumes of data to identify correlations and patterns and thus can be employed for predictive maintenance or warehouse management and material transportation in order to identify the most suitable and optimal routes considering the current circumstances and on-going conditions.