Frost & Sullivan research shows that the cross-pollination of ideas, technologies, and processes between the worlds of information technology and operations technology (IT-OT) is expected to form the crux of the fourth industrial revolution. The advent of advanced information and communications technologies (ICT) is likely to promote new interrelationships and interdependencies, giving way to unexpected business collaborations and partnerships in future. There is thus an increasing need for new value creation to realign synergies, partnerships, and collaborations across the vendor landscape.
The Measurement and Control Show 2015, organized by the Japan Electric Measuring Instruments Manufacturers’ Association (JEMIMA), focused on the increasing cooperation of information systems and control systems. The data acquired through Internet of Things (IoT) and heterogeneous control systems being capable of propelling innovation in the manufacturing environment, several Japanese companies presented their latest product development trends and insights into innovation with new data approaches in the Industrial Internet of Things (IIoT) landscape.
Yokogawa Electric Corporation, in particular, shared its IIoT deployment model for the effective use of huge volumes of industrial data. The evolution of IIoT enables control systems that have been used so far to be added to data production, thereby bringing about a major change in the manufacturing industry. Today, it is impossible to deal with the enormous amount of information only with advanced ICT platforms. Yokogawa thus emphasized the requirement for developing a “multiple knowledge” capability. In IIoT, the volume of data generated at the manufacturing site increases progressively. Therefore, analysing the information in real time and providing the data required by management authorities ensuring high accuracy and speed are key requirements that next-generation IOT systems need to address. Yokogawa laid emphasis on reducing the gap between the manufacturing site and management to improve management efficiency, speed up the decision-making process, and reduce business risks.
A better use of manufacturing data in IIoT is required in response to changes in manufacturing activities. There is a need for IIoT solutions that enable prompt management decisions in response to changes in product utilization. It is also important to understand the level of equipment utilization and monitor the expiration date for improving production planning. With such relevant data, companies can provide condition-based maintenance and predict equipment issues. Next-generation IIoT solutions thus need to focus not only on collecting and analyzing equipment data but also on other key areas such as production performance and connecting and integrating the information for optimal decision-making. There is the need for a strong focus on predicting equipment failure, proactive maintenance for integrated open systems, and proactive asset management, which allows for the best possible equipment plan.
Research indicates that for the achievement of IIoT, users are seeking reduced asset downtime and prompt services. Data required for maintenance are not usually collected. Some of the leading companies such as Yokogawa are developing data models to compare the current state of the manufacturing equipment with historical data.
According to Frost & Sullivan research, while mission-critical information, such as safety, financial, and operational data, continues to be strictly owned by end users, non-critical data are progressively being farmed out to solution and service providers. A platform approach that includes connecting, measuring, monitoring, managing, and monetizing data is required to seamlessly integrate silos and add value. Instead of adopting a diagnostic approach, where data are used to evaluate the root cause of a failure, the industry requires a more predictive approach with machine learning techniques to benchmark historical data with real-time sensor data, identify and detect anomalies in time, and minimize downtime.
Currently, a growing number of companies are working actively to change the future of the manufacturing industry, with a strong focus on providing increasingly proactive, predictive, condition-based maintenance to prevent any disruptions in the production process.
