IIoT provides three key benefits: industrial machines operate with more uptime; they provide more user feedback to increase efficiency and productivity, and they improve safety through process transparency. All of these are product of a successful transformation of data into tangible business value that ultimately creates higher margins for everyone involved.
It is time to collect and utilize valuable machine data. Instead of losing time by tediously gathering and verifying dispersed information and suffering from costly technical downtimes talpasolutions’ platform service offers powerful data management, predictive analytics and a platform for collaboration of heavy machine owners, users and manufacturers. Enabling fast and actionable insights based on machine data, our’ data expertise and domain know-how and your detailed process and asset expertise represents our deep conviction for joint success – an approach we call collaborative transformation.
The adoption of digital technologies is most efficient when it involves and integrates different users and activities/work flows throughout the value chain. By collecting and using data individually, different users create silos/islands of information. This leads to inconsistent and redundant data throughout the value chain. Organizations can make the most of big data by collaborating across the value chain. Big data of large machinery and facilities in the heavy industry is heterogeneous, as it comes from different systems, data sources, formats, standards, processes and tools. Integrating, normalizing and managing these data from the disparate sources is a crucial step to enable smart industry applications.
Machine data is omnipresent in daily work. A significantly increasing number of large equipment and facilities in the heavy industry are equipped with sensors and internal computing units which enable data-based controlling and monitoring. Such industries include mining, steelmaking, chemical and capital-intensive manufacturing industries.
However, for end users of such heavy machinery as well as their supplying OEM using large amounts of paper-based information or isolated excel files is rather the rule than the exception. Instead of voice over IP, 4G, email and messenger services the supervisors e.g. in many underground mines provide tasks to the operator by driving to the different workplaces or by two-way radio. Each morning it’s a challenge to find a mobile asset in a mine, as the last shift parked it somewhere and no localization data is available. Machines are used even though they urgently require planned or condition-based maintenance as a lack of transparency and diagnostics.
The problem of such capital-intensive industries is that they are using outdated rules of the game. Far too often a common approach is still investing in new machines and processes in an effort to improve end products. That’s a laudable aim, but it’s not enough. Especially at a time when volatile resource prices, shortages of skilled labor and increased supply chain and regulatory risks are accentuating an already volatile market. The answer for these heavy industries is the Industrial Internet of Things.
IIoT is embedding intelligence in industrial machines allowing them to be more efficient, self-detecting, safer, and connected, relieving mundane tasks from operators enabling them to focus on their remits and providing engineers and service personnel with hot data of machines’ condition and performance.
Transform data into business value