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Looking for a head’s up on what tech’s going to impact your business in 2023, so you can start planning? Well, we’ve prepared the list that you’re looking for. The good news is, you’ll already be familiar with each technology category listed. You might not have tested or deployed it, but now thanks to the progress of the hype cycle you have the benefit of evaluating the commercial benefits and making an objective purchasing decision.
Yes, we’ve been talking about this since 2011! But hey, this technology category is rapidly becoming more sophisticated. IoT technologies, such as sensors, edge computing, and data analytics connect industrial equipment and systems for real-time monitoring, control and automation. With proven benefits including improved efficiency, predictive maintenance, and operational cost reduction. Industry 4.0 encompasses these IoT technologies as well as artificial intelligence, digital twin and cloud computing to build “smart” factories and smart operations. Industry 4.0 is an ever-evolving strategy to continually optimize processes and lower the costs of production with data insights. Chances are, you’re somewhat down the line of implementing some but not all of these solutions.
AR technologies, such as heads-up displays and smart glasses, are increasingly being used in manufacturing, logistics, field services, inspection and maintenance to provide workers with real-time information and instructions overlaid on their physical environment. The technology can help improve worker productivity and safety – another example of how data-driven decisions are critical in every aspect of operations today. AR technologies are also being used to assist with employee training and development, with many large industrial companies adopting or evaluating the technology.
Robotics and automation technologies, such as drones and autonomous vehicles, are being implemented in industrial operations, manufacturing and maintenance to improve efficiency, maintain quality, reduce costs due to higher output, and enhance safety. This technology eliminates the risk of sending personnel into dangerous situations. The oil and gas industry is already using robots for seismic surveys, routine inspections and to resolve issues at their remote and dangerous off-shore platforms. The data collected can be quickly analysed and used for predictive maintenance. A strategic objective of many operators is to switch to unmanned sites and remote operations, and thanks to advances in this technology cluster, operators can do this sooner, often maintaining performance, reducing risk and operational costs.
AI and ML technologies continue to advance rapidly and are being used in a variety of applications in the industrial sector, such as predictive maintenance, anomaly detection, and process optimization. No-code and low-code platforms allow SME’s, engineers and operators to quickly build their own models based on their problem statement or performance objective. Models continuously learn from the plants data and provide real-time predictions and forecasting, alerting teams if an anomaly or fault is detected. AI and ML have a wide range of useful applications, and we will continue to see solutions emerge that address industry specific use cases. Here is a recent VROC case study of AI benefiting late life assets.
Unlike general-purpose cloud solutions, industry cloud platforms are designed for specific vertical industry segments, and incorporate services, tools and applications in one cloud platform to address hard-to-tackle challenges. Gartner estimates that by 2027 enterprises will use industry cloud platforms for 50% of business critical initiatives. These turn-key platforms include industry-specific functionality and are adaptable to business needs which helps accelerate time to value. You are probably some-what cloud-based these days, and this is just set to continue across your operations.
At the end of 2022 it was hard to miss OpenAI’s product ChatGPT. For many, this was the first real experience with Generative AI language models. An easy-to-use method for generating content, solving questions and even writing computer code. How will this new tech impact industrial operations? Well first of all, non-data science users may be able to use Generative AI to produce plans to execute a particular task, or for writing, documenting and reviewing code, as well as to help answer complex questions from vast amounts of written and visual data. This may help improve efficiencies; however businesses need to use caution as answers provided may not be entirely accurate, may include bias and will most likely lack the nuances of a company’s values and culture.
These seven tech trends are not going to be applicable for every industrial business, and even if there is a valid use-case, it may not be large enough to generate savings necessary when weighed against the cost of implementation and effort required. So how do you know if it worth pursuing?
1. What pain point are you trying to solve, and what is its current cost to the business?
2. Is the solution interoperable with your existing ecosystem?
3. What is the effort required to integrate the solution?
4. What benefits are you expecting from the solution, and in what time-frame?
5. How do you plan to track and measure success?
6. How much change is required to current processes? How can you assist with change management?
7. What is the cost of implementation and on-going cost of the solution?
Before implementing, is there a pilot project you can use to evaluate the solution? If so, go through the above questions just for this pilot project.
If you find that the solution is not interoperable with your existing ecosystem but you still deem it worthwhile, it may be time to revisit your existing tech stack. Many organisations find that legacy infrastructure and fragmented data storage can hinder the ability to scale the use of technology, such as machine learning. Getting the business aligned with its architecture design, security and data governance, and utilising an infrastructure that can support the business both now and into the future is a critical first step to any digital transformation.
It’s an exciting time to be able to solve business operational challenges through the use of technology. We hope that these top tips help you make a successful tech purchasing decision and lead to business improvement and long-term cost savings.
Four factors to consider when choosing a predictive maintenance solution for your manufacturing or process plantRead Article
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