TIBCO® Connected Intelligence for Smart Factory Insights
By processing real-time data from machine sensors using artificial intelligence and machine learning, it's possible to predict critical events and take preventive action to avoid problems. TIBCO helps manufacturers around the world predict issues with greater accuracy, reduce downtime, increase quality, and improve yield.
Today, you can improve product quality and gain better control of the entire
manufacturing chain with data virtualization, machine learning, and advanced
data analytics. With all relevant data aggregated, analyzed, and acted on, sensors,
devices, people, and processes become part of a connected Smart Factory
•? Increased uptime, reduced downtime
•? Minimized surplus and defects
•? Better yields
•? Reduced cost due to better quality
•? Fewer deviations and less non-conformance
Published By: Panasonic
Published Date: Oct 01, 2019
For manufacturers, the transition to Industry 4.0 has meant the accumulation of data, massive data. Indeed, the accumulation, distribution and evaluation of data are driving virtually every decision on the manufacturing plant floor and supply chains shaping those decisions. Given the striking fact that ninety percent of the data in the world has been created over the last two years, it isn’t surprising that more than 60 percent of large companies report having a Chief Data Officer. But what has opened the floodgates to this deluge of information in manufacturing? Ordinary sensors have been transformed into smart sensors with the advent of IoT technologies and are being deployed by manufacturers along every step of the supply chain. Sensors are now detecting everything from when a piece of equipment will need maintenance to controlling energy costs inside factories.
IoT describes a system where items in the physical world, and sensors within or attached to these items, are connected to the Internet via wireless and wired Internet connections. These sensors can use various types of local area connections such as RFID, NFC, Wi-Fi, Bluetooth, and Zigbee. Sensors can also have wide area connectivity such as GSM, GPRS, 3G, and LTE.
The Industrial Internet of Things (IIoT) is flooding today’s industrial sector with data. Information is streaming in from many sources — equipment on production lines, sensors at customer facilities, sales data, and much more. Harvesting insights means filtering out the noise to arrive at actionable intelligence.
This report shows how to craft a strategy to gain a competitive edge. It explains how to evaluate IIoT solutions, including what to look for in end-to-end analytics solutions. Finally, it shows how SAS has combined its analytics expertise with Intel’s leadership in IIoT information architecture to create solutions that turn raw data into valuable insights.
For many of us, the term “smart city” conjures up images of sensors
collecting data about everything from traffic patterns to energy use.
It’s common for government leaders to think, “That’s not for us.
We’re not there yet.” But if your organization is collecting data of any
kind, you are in a position to use that data to create a smarter city for
Download this whitepaper for 10 examples of analytics being used to solve problems or simplify tasks for government organizations.
For organizations to succeed with the onslaught of devices, sensors and tools that innovation garners, data must no longer be treated as a byproduct but instead as an asset. And data-driven innovation must start at the top. That's what Michael Schrage, Fellow at MIT Sloan School's Initiative on the Digital Economy, said during the Harvard Business Review webinar, Leadership and Big Data Innovation. Find out why data experimentation, governance and culture are part of the next leadership challenge for organizations.
HPE InfoSight analyzes millions of sensors every second to predict and prevent problems across the infrastructure stack and transform the support experience. Based on ESG research, the benefits to enterprises stemming from HPE InfoSight are both significant and unique.
By processing real-time data from machine sensors using arti?cial intelligence and machine learning, it’s possible to predict critical events and take preventive action to avoid problems. TIBCO helps manufacturers around the world predict issues with greater accuracy, reduce downtime, increase quality, and improve yield.
The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution.
Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze.
Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform.
Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing:
• Reduced downtime
• Minimized surplus and defects • Deep insights
• End-to-end real-time visibility
The Internet of Things (IoT) presents an opportunity to collect real-time information about every physical operation of a business. From the temperature of equipment to the performance of a fleet of wind turbines, IoT sensors can deliver this information in real time. There is tremendous opportunity for those businesses that can convert raw IoT data into business insights, and the key to doing so lies within effective data analytics.
To research the current state of IoT analytics, Blue Hill Research conducted deep qualitative interviews with three organizations that invested significant time and resources into their own IoT analytics initiatives. By distilling key themes and lessons learned from peer organizations, Blue Hill Research offers our analysis so that business decision makers can ultimately make informed investment decisions about the future of their IoT analytics projects.
Massive amounts of data are being created driven by
billions of sensors all around us such as cameras, smart
phones, cars as well as the large amounts of data across
enterprises, education systems and organizations. In
the age of big data, artificial intelligence (AI), machine
learning and deep learning deliver unprecedented
insights in the massive amounts of data.
Amazon CEO Jeff Bezos spoke about the potential of
artificial intelligence and machine learning at the 2017
Internet Association‘s annual gala in Washington, D.C.,
“It is a renaissance, it is a golden age,” Bezos said.
“We are solving problems with machine learning and
artificial intelligence that were in the realm of science
fiction for the last several decades. Natural language
understanding, machine vision problems, it really is
an amazing renaissance.” Machine learning and AI is a
horizontal enabling layer. It will empower and improve
every business, every government organization, every
Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data
In our increasingly connected world, quality, reliability and
consistency matter a great deal, particularly in the context of the
smart home ecosystem. The antennas, connectors, relays,
sensors, switches, terminals and tubing inside these devices
play critical roles in the product’s ultimate functionality. If you
don’t focus on the right components or choose the wrong or
incompatible ones, then device reliability becomes an issue.
Maintaining a competitive edge today means building a Digital Enterprise capable of taking full advantage of social, mobile, web, cloud, “things,” (sensors and devices), and analytics technologies. Among the terms used to describe this business transition is “the API Economy,” an economy in which APIs are no longer just an IT concern, but the underpinnings of new revenue streams and new business models that are disrupting entire industries.
Read this paper to learn about:
New, modern applications being built for the enterprise
Application ecosystems and extending the value of your company in the API Economy
Two ways to integrate devices in the Internet of Things
The microservices approach to application development
The role of API management in the digital enterprise
IT organizations using machine data platforms like Splunk recognize the importance of consolidating disparate data types for top-down visibility, and to quickly respond to critical business needs. Machine data is often underused and undervalued, and is particularly useful when managing infrastructure data coming from AWS, sensors and server logs.
Download “The Essential Guide to Infrastructure Machine Data” for:
The benefits of machine data for network, remote, web, cloud and server monitoring
IT infrastructure monitoring data sources to include in your machine data platform
Machine data best practices
Today’s tech savvy consumers are continually driving organizations to deliver a modernized shopping experience. To achieve this, retailers are pushing the edge on developing non-traditional ways in delivering sales messages. One of the best ways to engage shoppers with an in-store digital presence is through modern adaptive signages.
Modern signages enable two-way interaction between customers and businesses, tapping onto cutting-edge technologies such as sensors and analytics to respond to customer behavior—helping retailers customize content on the fly.
Find out how Giada Technology leveraged on Intel® processors to power up their cloud terminals to pre-process signage, sensor, and mobile data to efficiently exchange information with the cloud. Retailers are better positioned to present contextual promotions to the shoppers, delivering benefits of lesser wait-time and increased customer satisfaction.
Robots play a key role in achieving manufacturing efficiencies and reducing labor intensive operations across diverse industries. Traditional machine vision has its limitations, however—typically, it can only conduct defect detection and classification based on fixed rules and work in fixed environments. To add on, the complexity of robotic system design poses challenges for many manufacturers to identify and integrate subsystems from multiple vendors.
The future of robot and machine solutions is a production environment where devices, machines, robots, and sensors are interoperable.
Find out how NexCOBOT integrates AI-driven vision capabilities into robotics to improve quality and accuracy over traditional machine vision—as well as providing an open and modular solution for users to develop a robot control system that best fits their particular application requirements.
More sophisticated cameras and vehicle sensors are enabling new ADAS features and the deployment of highly autonomous vehicles. However, reactive decisions and camera-based systems struggle when lane markings fade, snow or dirt covers the road, and the environment changes.
Map-based Lane Keeping with HERE HD Live Map from VSI Labs examines how HD map assets can improve the safety and performance of automated vehicle features.
Download this free report to learn:
• How map data improves the performance and safety of ADAS features
• How map-based systems outperform computer vision only system
• The architecture of VSI’s map-based lane keeping system
With urbanization set to increase rapidly – the UN predicts that by 2050, 68% of the world’s population will live in urban areas – discover how, with HERE, you can keep your city moving. And make it more safe, efficient, and green.
HERE is already working with governments around the world to keep traffic flowing and pollution down. In this guide, discover how, with our growing network of sensors and over 30 years’ experience, we can deliver the real-time insights to keep you abreast of what’s actually happening on your roads, so you can better meet government safety and mobility targets.
The Internet of Everything (IoE) is a continuous interaction among people, processes, data, and things. Sensors, networks, and smart devices are ubiquitous, providing a torrent of streaming data or big data. The Internet of Things (IoT), which is a network of physical objects accessed through the Internet that can sense and communicate, is a component of IoE.
Cisco is helping customers and strategic partners leverage the full potential of IoE to achieve radical results across all sectors and industries. Indeed, IoE is capable of helping public safety and justice agencies increase cost efficiency, improve safety and security, provide better response times, and increase productivity.
Smart technologies are a force multiplier for public safety agencies, allowing them to serve growing populations even as public spending remains constrained. The Internet of Everything (IoE) provides the connective tissue in this evolving operational environment — not only bringing together objects embedded with electronics, software and sensors, but making them work together in the service of better policing.
The IoE makes it possible to collect data and share it via the cloud, uniting disparate jurisdictions, agencies and ranks of command in positive ways. These smart and connected technologies promote collaboration and transparency among public safety agencies, revolutionizing how police, fire, courts and corrections do some of the nation’s most important work.
The transformation of supply chain management is happening now. IoT is driving that change, but supply chain analytics is instrumental in taming the massive amounts of data generated by IoT sensors, devices and objects and turning it into insight and into a competitive edge. Smart companies recognize this.
Part 3 in our Partnering with Certainty Webinar Series, "Customer Demands at the Edge."
As distributed edge environments become more critical, physical security becomes more important. Nobody would leave their data center wide open for anyone to enter, but that’s exactly how many organizations treat their edge computing sites. Often, they consist of a rack or two of gear in a non-dedicated location, perhaps a janitor’s closet, with little to no physical security.
Fill out your information and click "Register" to watch the third event in our Partnering with Certainty Webinar Series, “Customer Demands at the Edge: Protect me from Downtime!” This webinar originally aired on November 9th, 2017.
In this webinar, we discuss physical security best practices, including environmental issues such as temperature and humidity monitoring. We also update partners on the physical security features of the latest APC racks and the NetBotz line of security and environmental appliances, cameras and sensors.