Four Considerations for Manufacturing with the IIoT
With global spending on IIoT expected to reach $745 billion in 2019, industries continue to gear up for Industry 4.0. According to International Data Group (IDC), that number represents an increase of over 15% from 2018, and double-digit growth is expected to continue through 2022. Leading the pack are discrete manufacturers and process manufacturers who are expected to spend $119 billion and $78 billion respectively.
The constantly changing world of the IIoT has yet to settle upon a stable or standardized infrastructure, as both capabilities and service offerings continue to be added. Additionally, those functions of IIoT recognized as core technologies not only continue to advance, they are also beginning to overtake many single purpose platforms such as MES to offer alternatives.
With this level of disruption, it can be confusing to many and easy to overlook the value and services both current and on the horizon. Here are a few considerations to consider with the Industrial Internet of Things in today’s – and tomorrow’s – manufacturing environments:
1. Analytics Architecture is Opening Doors to New Services
The power of deep and advanced analytics in the IIoT has always been one of its biggest advantages. But as these capabilities improve, new software and services are being rolled out to take full advantage of analytics.
This is true of both shop floor operations as well as maintenance and supply chain. Human-based monitoring and analysis is often undertaken in hours, shifts, days or weeks. But operationally, a connected factory can perform the same monitoring on a minute by minute or second by second basis. This depth of analysis allows operators to address downtime and quality issues quickly and accurately through alarms and Pareto charts for any time period to help mitigate bottlenecks. For most platforms, this analysis extends to setup and changeover times to identify areas for improvement.
For maintenance and OEE, conditions-based monitoring is proving to be a powerful analytical tool to improve quality and reduce maintenance costs, unexpected downtime and part cost. Sensors can record sound, vibration, temperature and other variables and analytics can determine the condition of the part to determine if it is working within optimal condition. Real-time automated OEE reporting and operator and staff dashboards are dynamic and allow staff to adjust in real-time rather than after the fact.
Already, the improvement in analytics architecture has spurred new design iterations to take advantage of the wealth of data gathered by connected equipment. And as analytics advance, the architecture of analytics platforms will continue to allow new service levels for these features as well as new services to be added as well.
2. IIoT Platforms are Beginning to Converge and Overtake Traditional Software Applications
Industrial IoT applications are already capable of integrating with traditional software applications such as ERP, MRP, MES, OEE software and finance software to leverage the power of collected data to improve decision making.
But things may be at a tipping point. IIoT platforms today can already provide asset management, real-time conditions-based monitoring, and utilization reporting for equipment. On the shop floor, fixed and mobile devices with KPI displays, customized dashboards, and notifications allow dynamic reaction to issues in real-time. These platforms use open APIs to expand the versatility to feed directly into the platform’s analytical capabilities.
With such a wide range of opportunity to address manufacturing operations under a single system, it is only a matter of time before IIoT systems move from being integrated and complementary to other software to being the primary driver. At that point, older software applications would in the least be redundant, and would perhaps be unnecessary as IIoT technology replaces them.
3. Production Efficiency and Mode of Production
All manufacturers place primary emphasis on production efficiency. Through the use of lean methodology in production, Six Sigma and other programs, manufacturers at the end of the last century were able to bring about remarkable improvements in production efficiency. Those relying on IIoT platforms today are no less focused on efficiency to unlock the “hidden factory” capacity that is possible. Studies show that 43.1% of companies rely on platforms to achieve process optimization while another 41.1% use general dashboards and visualization.
Improved visibility has been shown to increase production efficiency by as much as 20% in a connected factory. With real-time machine monitoring, predictive notifications and advanced analytics, that visibility is achieved through customizable dashboards in both fixed and portable displays. This allows operators, technicians and managers to have a powerful view of what is happening around them and gives them the capability to be proactive in their decision making.
Manufacturing IIoT platforms are beneficial to any mode of production. In traditional software applications or manual monitoring, the quality of analysis degraded as complexity of product increased. Accurate analysis, when possible, was often time consuming and dated by the time it could be completed. With IIoT platforms, the volume of data collected from sensors, combined with deep analytics, advanced machine algorithms, and AI allow for accurate visibility and actionable information regardless of the complexity of the operation. This is true for all modes of production but especially true for discrete manufacturers who are often tasked with finding efficient means of producing small lots to remain competitive. The use of IIoT platforms allows these manufacturers to identify workflow and process inefficiencies to address.
4. Security Still Foremost on Manufacturer’s Minds
Studies have shown that only one in three companies have undertaken new security technology for their IIoT deployments. This leaves a high number of enterprises at risk. This is especially critical given that experts suggest building security in at the ground level of the IIoT infrastructure in any company.
The issue is complicated further in that many manufacturers do not possess the skills to undertake an overhaul or replacement of their current security. One study has shown that as high as 56% of companies lack the skills to address cybersecurity to fully deploy their company’s IIoT solutions. For those that began their IIoT transformation early on, most consider security of the system as more important than even the scalability of the system as benefits begin to be realized.
The use of Industrial Internet of Things technology has the potential to deliver greater gains in efficiency, cost and profitability than its counterparts such as lean and Six Sigma in the latter part of the 20th Century. Coupled with production floor visibility, conditions-based monitoring and process optimization, manufacturers are already seeing significant benefits. But every producer should be aware that Industrial IoT is still at the beginning. With each passing month, new advances in computing, improvements to algorithms, gains in AI and sensor and device improvement will continue to open the door for even greater improvements to existing services as well as pave the way for new value-added services and capabilities as well.
Originally this article was published here.
This article was written by Graham Immerman, the Director of Marketing for MachineMetrics, a venture-backed manufacturing analytics platform. Graham has quickly become an authority on digital transformation and the application of IIoT technology for the manufacturing industry. An accomplished leader and experienced start-up veteran with an integrated background in digital, social, traditional, account-based marketing, growth strategies, and business development.