Global Vice President of Industry Solutions at Neudesic, an IBM Company
Answered a year ago
On a recent project with a manufacturing client, real-time data integration saved the day when an issue in production would just show out of the blue. We had worked with the customer, to install IoT sensors right across their production line, feeding live data into a centralized system powered by Azure IoT Hub. That very day, the dashboards flagged some unusual spikes in temperature and pressure on one of the key bottling machines. If it hadn't been for this early warning, the problem which was a faulty valve could have gone undetected, with a potential loss of hours of production and wasted products. Because of real-time notifications and data visualization, the customer's team acted in an extreme agile fashion. An automated workflow via Microsoft Teams warned maintenance staff in the blink of an eye who were able to inspect and repair the valve within the hour. No major downtime, no product spoilage-just a rapid response and seamless recovery. With the Real-time IoT data, cloud-based analytics, and automated alerts, the disruption that could have been serious was minimized to a small speed bump. It's great to note solutions like this have such a tangible effect. In addition, it reinforces just how important it is for operations teams to have access to real time notifications and alerts. This pattern is becoming a blueprint for future implementations, not only with this client, but with other manufacturers desiring improvements in efficiency and resilience.
Our Asia-based client, operating multiple facilities across various countries, is expanding from a low-volume job shop to a large-scale global operation handling thousands of jobs. They understood that using data and digital technology was necessary for investigating machine usage, identifying the causes of downtime, and addressing quality issues, since the old manual tracking system was slow and prone to mistakes. On the whole, the team wanted to combine and organize data from different machines, shop-floor systems, and manufacturing sites that had been previously disconnected, aiming for full production transparency and useful insights. 1. Challenges One of the primary challenges they encountered was the absence of real-time data. Relying on manual data collection methods, such as waiting for operators to return from shifts, proved to be time-consuming and inefficient. They also struggled to gather comprehensive data across different shifts and time periods, rendering it difficult to draw accurate conclusions and determine the underlying causes of machine downtime and performance variations. Without real-time data and a systematic approach to root cause analysis, it was challenging to pinpoint the exact reasons behind issues such as machine failures, tooling problems, or operator errors. 2. Solution To enhance production efficiency and gain valuable insights into operations, we implemented a comprehensive digitalization platform, deploying sensor hardware and software throughout our factory to collect real-time data from machine controls and operators. Our digitalization strategy included the following components: - Data Collection: Sensors and software gathered data on machine conditions, job progress, and operator activities to track OEE-related metrics. - Real-Time Dashboards: Dashboards mounted on the factory floor provided a visual representation of production performance, enabling managers to quickly identify issues and make informed decisions. Touchscreens at each machine help operators track their performance, identify bottlenecks, and contribute to process optimization. - Advanced Analytics: Our analytics present insightful summaries of production data, quantify specific machining operation effectiveness and identify areas for further optimization. - Data Integration: The solution's open APIs facilitated data aggregation across various shop-floor systems, enabling a more holistic view of operations.
A few years ago, we had a scenario where real-time data from our integrated health management systems allowed us to quickly spot and address an emerging postural issue that could have led to more severe injury. An athlete client came in with vague upper back pain, but without any specific incident or trauma. Using our integrated electronic medical records and movement-tracking technology, we could assess his biomechanics in real time. The data showed a progressive change in his posture over weeks, pinpointing that his pain was a direct result of a misalignment rather than a typical strain. With this information, we were able to act swiftly, implementing an adjustment program that combined targeted physiotherapy, Pilates, and specific ergonomic changes. This interdisciplinary approach, supported by real-time insights, allowed us to resolve the issue before it worsened, keeping the athlete in peak condition. My background, with over 30 years in physiotherapy and experience working closely with athletes, was instrumental here. Years of analyzing movement patterns and a solid foundation in musculoskeletal assessment enabled me to interpret the data rapidly and create a tailored treatment plan. The critical technology in this case was our EMR system combined with movement analysis tools, allowing for seamless, instant data integration that informed our next steps without delay. This experience underscored the power of combining hands-on expertise with cutting-edge technology to drive optimal health outcomes.