Industry 4.0 technology roll-out in 2020 is still low, with less than 30% of manufacturers reporting extensive adoption today -– this is a key finding of IoT Analytics' latest 286-page Industry 4.0 & Smart Manufacturing Adoption Report, published in January 2020. IoT Analytics performed an extensive, in-depth survey of 150 IT and OT decision makers from some of the leading manufacturers around the world in order to better understand Industry 4.0 adoption across regions, industries, use cases and technologies. Among other things, IoT Analytics asked respondents to comment on the current and future adoption of the following 17 Industry 4.0 technologies: In addition to Industry 4.0 adoption, respondents were asked to comment on Industry 4.0 technology ROI, spending (current and future), preferred vendors, use cases, success factors, architectures, communication protocols and various other things. The following 4 findings highlight some of the answers pertaining to the question "Who is ahead in Industry 4.0 adoption?" North America is clearly leading Europe and Asia when it comes to overall Industry 4.0 adoption, with 36% of respondents indicating the Industry 4.0 technology was either "extensively" or "fully" rolled out in operations.
Apache Kafka, the open source distributed messaging system, has steadily carved a foothold as the de facto real-time standard for brokering messages in scale out environments. Confluent, the company whose founders created Kafka, has just released their third annual report on implementation. The report reached a much bigger sample, hinting at growth, while showing some modest changes in how Kafka is being used. Gartner analyst Merv Adrian's point that in Silicon Valley, if an idea is on a whiteboard, it must be commonplace could apply to Kafka. There are alternatives: MapR Streams allows you to broker messages without requiring a separate Kafka cluster, while streaming services such as Amazon Kinesis Firehose offer similar capabilities.
Cognitive computing services might include everything from predictive maintenance to customer experience and medical diagnoses. According to a recent report from Allied Market Research, the cognitive computing market is expected to generate revenue of $13.7 billion by 2020. On top of that, IBM CEO Ginni Rometty recently told CNBC that Watson would reach more than 1 billion consumers by the end of 2017. The cognitive computing market is growing in size and complexity--and quickly. IBM defines cognitive computing as a set of "augmented intelligence" capabilities that include machine learning, reasoning and decision technology, language, speech and vision, human-interface tech, distributed and high-performance computing, and new computing architectures and devices.
And this may just be the next evolution of the operating system. Cognitive computing services might include everything from predictive maintenance to customer experience and medical diagnoses. According to a recent report from Allied Market Research, the cognitive computing market is expected to generate revenue of $13.7 billion by 2020. On top of that, IBM CEO Ginni Rometty recently told CNBC that Watson would reach more than 1 billion consumers by the end of 2017. The cognitive computing market is growing in size and complexity--and quickly.
The fourth industrial revolution is firmly upon us and it is one that will provide customers with a greater range of customized products and a better service experience, while allowing manufacturers to transition towards predictive and adaptive processes and machinery. Artificial intelligence (AI) is not a peripheral component of this industry change; it is at the heart of the fourth industrial revolution, a key enabler to take the step from automation to autonomy, creating growth and competitive advantage. Together with Industry of Things World, Europe's leading Industrial IoT conference, HPE surveyed 858 predominantly European professionals and executives from various industrial verticals to find out what effect AI has in the industrial sector today and is expected to have by 2030. Their responses show that the European industrial sector has clearly understood and embraced the strategic power of AI--but it also reveals that there are some key challenges that have to be overcome to fully unleash its potential. Let's start with the really good news.