INSPIRATION
From supply chain management to maintenance scheduling the process of capturing and storing data is critical to ensure agility in the manufacturing system. The data in a manufacturing company consists of information regarding assets, materials, processes, and customer feedback all in different formats and protocols. For this myriad of data,the conventional methods of data handling are inefficient in performing predictive and advanced analytics. Here big data analytics systems with machine learning algorithms are one of the manufacturing trends that finds patterns and provides real-time insights. The vast amount of data that these analytics platforms process improves safety, enhances efficiency,simplifies product innovations, and reduces costs to a greater extent.
DatenBerg (2018, Munich, Germany) is a German startup that uses big data analytics to simplify the decision-making process of complex production processes. The startup’s software uses data from multiple sources and consolidates it to visualize, compare and evaluate them. The solution finds
relationships between input data (e.g. material data or machine parameters) and quality features of the product, which enables process improvements. The AI algorithms of the big data platform generate predictive models that intelligently control the process. The proactive interventions from the solution help manufacturing companies prevent rejections and machine downtime.
Technotery (2017, Ahmedabad, Gujarat) is an Indian startup providing turnkey IT solutions for multiple industry verticals. The software solution converts raw data from multiple sources on the manufacturing unit into a usable format.This data translates into an input for data visualization and business intelligence tools leading to a better understanding of the operational data. Technotery helps businesses in the
manufacturing industry determine Key Data Indicators (KDI) and uncover hidden trends and patterns from large amounts of data. The startup’s solution leads to more effective maintenance management, higher operational efficiency, and better cost reduction.
