Introducing Advanced Connectivity with Wi-Fi on the go

Imagine a fully functioning and connected office on the go. Access to multiple entertainment and business applications from within your vehicle is now available as the British car manufacturer, Bentley, announced the offering of the first in-car Wi-Fi system.

All Bentley models in 2019 will be presenting drivers and passengers the ability to connect to the Bentley Advanced Connectivity system using a dedicated app on their smart phone. User friendly applications include the ability to access and edit files, hold video conferences, connect to virtual meetings, and benefit from Bentley Skype for Business.

Behind Bentley Advanced Connectivity

An exclusive contract has given Bentley a head-start in Wi-Fi on the go for at least 12 months. Partnering with internationally recognized communication company, Viasat, the manufacturer produced a multi-channel virtual private network (VPN) capable of supporting up to three mobile network operators. Style and comfort are not compromised with the connectivity system placed inside the vehicle’s boot lid, and the router connected to the on-board DC power supply.

Bentley IoT Security

Multiple layers of security and in place as data transferred with Bentley Advanced Connected is reconsolidated for the end user after being divided and transmitted over three mobile networks. One compromised SIM card would therefore not alarm a security breach as it represents only part of the data package. Furthermore, Active Cyber Defense, a system developed to protect users from data theft and ransomware attacks offers additional layers of support and security. On-the go secure connectivity is being made possible through technology and comfort.

What does the future of driving with Wi-Fi look like?

How does IoT enhance one’s driving experience?

Is data security compromised with on-the-go Wi-Fi?

Sources:

https://www.bentleymotors.com/en/world-of-bentley/the-bentley-story/news/2018-news/bentley-introduces-worlds-first-super-fast-in-car-wifi.html

https://www.iottechnews.com/news/2018/nov/05/bentley-launches-car-wi-fi-system-advanced-connectivity-uninterrupted-mobile-network/

 

 

Augmented Reality & Supply Chain Management

An article published on the APICS website describes five ways augmented reality enhances supply chain management, as derived from a 2016 partnership between DHL and augmented reality hardware companies and software providers. DHL found that partnering with Vuzix and Google, as well as Ubimax to test incorporating AR in logistics activities positively impacted worker efficiency and reduced error rates leading to an average 15% improvement in productivity. In addition to providing logistics solutions, DHL is testing the application of AR in operations, warehousing, and logistics in order to capture more of the streamlined work efficiencies and reduced error rates at the individual and enterprise level from incorporating technology. ABI Research released the following top-five benefits of using AR in supply chain management.

Efficiency increases: The virtual communication of next steps in performing tasks frees up workers’ hands increasing overall efficiency in performance. Instead of flipping through instruction manuals, workers can see the information necessary to complete tasks in their fields of vision using smart glasses.

Cost reductions: AR enhances instant communication by enabling remote users to see what the wearer is seeing. Travel expenses and downtime can be reduced by circumventing the need for individuals, such as offsite managers, consultants, or manufacturers to be physically present.

 Safety improvements: Safety warnings in the wearer’s field of vision coupled with the worker’s hands free from holding instruction manuals, enable users to be more focused and potentially avoid distractions or injuries.

Error minimization: Virtual models and instructions are available in the user’s field of vision providing real time directions for completing tasks. Errors can thus be minimized by the visual clarity and instant feedback provided.

Fast ROI: AG enhances the ROI of training employees, accessing information, finding solutions and completing tasks by immediately pulling up answers on the smart glasses. Guidelines, checklists or diagrams are quickly available in the user’s field of vision leading to employees being more productive.

+6th AR benefit: The 4G or 5G connectivity available for certain AR devices enables employees to receive guidance anytime, anywhere. Continuous remote connectivity could continue to grow as cellular wireless AR develops.

How can manufacturing companies and employees benefit from AR?

What are examples of AR tools that can enhance Supply Chain Management?

How does AR improve employee performance?

APICS – Five Ways Augmented Reality Enhances Supply Chain Management

 

Internet of Things: Transforming the Industry

Its not just limited to smart phones anymore. Smart things have reached the masses. Products with wireless connectivity (from lightbulbs to thermostats to smart speakers) are more present in people’s homes today than not. A report suggests that 79% of U.S. consumers have at least one connected device at home.

But this technology actually has its roots in a world that predates the rise of remote control gadgets: industrial manufacturing.The (Industrial) Internet of Things takes networked sensors and intelligent devices and puts those technologies to use directly on the manufacturing floor, collecting data to drive artificial intelligence and predictive analytics. The IOT is driving an industry that has struggled in recent years due to talent shortages, and this offers hope for the industry’s future. It can transform traditional, linear manufacturing supply chains into dynamic, interconnected systems—a digital supply network (DSN)—that can more readily incorporate ecosystem partners. It is helping to change the way that products are made and delivered, making factories more efficient, ensuring better safety for human operators, and more often than not saving millions of dollars.

One of the greatest benefits of the IoT is how it can exponentially improve operating efficiencies. If a machine goes down, for instance, connected sensors can automatically pinpoint where the issue is occurring and trigger a service request. It can also help a manufacturer predict when a machine will likely breakdown or enter a dangerous operating condition before it ever happens. It is largely proactive in its functioning. It enables predictive maintenance, which limits the equipment downtime and improves safety. The sensors work by analyzing a given machine to tell if it’s working within its normal condition. This process—known as condition monitoring—is time intensive when we humans do it manually. But by using sensors to collect and quickly analyze data points in the cloud, prediction becomes easier.

Beyond saving money and time, the IoT can keep workers safe. If an oil well is about to reach a dangerous pressure condition, for example, operators will be warned well before it explodes. Sensors can even be used to manage and monitor workers’ locations in case of an emergency or evacuation.

Q1) How is IOT changing the status quo in industries?

Q2) How does IOT help in predictive maintenance ?

Q3) How is IOT improving efficiencies in manufacturing ?

source:https://wordpress.com/post/dcmme.wordpress.com/1921

 

IOT in Supply Chain

The process of assessing a chicken in real-time before agreeing to eat it may seem a bit outlandish. But with the IoT, we’ll be able to experience that type of transparency, and so much more. IoT is set to revolutionize the supply chain with both operational efficiencies and revenue opportunities made possible with just this type of transparency. In today’s market, supply chain isn’t just a way to keep track of your product. It’s a way to gain an edge on your competitors and even build your own brand.

 

With the ever advancing IOT we will be seeing changes in the following areas

 

 

Operational Efficiencies

 

When it comes to operational efficiencies, the IoT offers many:

 

Asset Tracking: Tracking numbers and bar codes used to be the standard method for managing goods throughout the supply chain. But with the IoT, those methods are no longer the most expedient. New RFID and GPS sensors can track products from floor to store. At any point in time, manufacturers can use these sensors to gain granular data like the temperature at which an item was stored, how long it spent in cargo, and even how long it took to fly off the shelf. The type of data gained from the IoT can help companies get a tighter grip on quality control, on-time deliveries, and product forecasting.

 

Vendor Relations: The data obtained through asset tracking is also important because it allows companies to tweak their own production schedules, as well as recognize sub-par vendor relationships that may be costing them money. Up to 65% of the value of a company’s products or services is derived from its suppliers. That’s a huge incentive to pay closer attention to how your vendors are handling the supplies they’re sending you, and how they’re handling your product once it’s made. Higher quality goods mean better relationships with customers—and better customer retention overall.

Forecasting and Inventory:  IoT sensors can provide far more accurate inventories than humans can manage alone. For instance, Amazon is using WiFi robots to scan QR codes on its products to track and triage its orders. All the data can be used to find trends to make manufacturing schedules even more efficient.

Connected Fleets: As the supply chain continues to grow—upward and outward—it’s even more imperative to ensure that all your carriers—be it shipping containers, suppliers’ delivery trucks, or your van out for delivery—are connected. Data is the prize. Just like cities are using this data to get to emergencies quicker or clear up traffic issues, manufacturers are using it to get better products to their customers, faster.

Scheduled Maintenance: The IoT can also use smart sensors on its manufacturing floors to manage planned and predictive maintenance and prevent down-time and cut costs.

 

 

Revenue Opportunities

The chance to know more—and understand more—about our customers, their buying habits, and the trends associated with them is invaluable. It allows businesses to form tighter connections with customers and, inevitably, market to them in new and better ways. Beyond the use of data for improved efficiencies noted above, businesses can get creative with supply chain transparency. They can build a reputation of social responsibility by allowing customers to access—and with AR, even see—where their product came from, who made it, and the conditions in which those workers lived.

Research shows 70% of retail and manufacturing businesses have already begun to transform their supply chain processes. However, when it comes to supply chain, there is far from a level playing field. For the IoT to be truly effective, all members of one’s global supply chain must be connected. In an age when many companies are just now embracing the concept of mobility, that may take a while. Still, as technologies like blockchain and edge computing continue to take form, there is so much further we can go to make our supply chain even more efficient—and creative—than ever before. Perhaps that’s where the real excitement lies.

 

 

https://www.forbes.com/sites/danielnewman/2018/01/09/how-iot-will-impact-the-supply-chain/#15bf17393e37

 

Q) When will IOT really begin to have an impact on supply chain operations?

Q) What are the other opportunities and applications of IOT in supply chain?

Q) What are the major challenges faced by companies in implementing IOT in supply chain?

Process Mining – Big Data Working for Manufacturers

In the article Why Manufacturers Need Process Mining – A New Type of Data Analytics, the author is extolling the benefits of what he calls a new type of data analytics – process mining.  Process mining can be used to reduce inventory costs, identify production bottlenecks, improve on-time delivery, and optimize logistics between production sites, distribution centers, and end clients.  It’s hard to justify  that process mining is actually a new type of data analytics that can be used for manufacturers, but process mining does follow the a few of the key rules for successful big data usage.  First, as the name implies, it concentrates on one process.  Implementation of successful big data projects normally requires concentration on one area for improvement.  The specificity of big data projects usually allows them to be successful, and the article looks at why process mining, and big data analytics on the whole, can be successful in saving manufacturers money.

Process mining specifically looks at a very important factor in manufacturer’s processes, KPIs or key performance indicators.  KPIs are exactly what they sound like, the main factors that measure performance and the overall successfulness of process or project.  Process mining’s value lies in the fact that it initially makes one look at KPIs of a process.  It also challenges the manufacturer to validate if they are measuring the right KPIs and understand if the data they are gathering can be related back to KPIs.  Process mining, as all big data does, uses software do the difficult work of visualizing the processes and highlighting specific variances impacting KPIs.  One example used in the article is the examination of throughput times and the ability to identify that specific vendors are not meeting their lead-time commitments.  These types of analyses and results is exactly what big data projects are meant to do and achieve.

Another point that the article points out is that process mining encourages manufacturers to identify inefficiencies and problems within the process.  It encourages companies to embrace their issues.  This ideology is absolutely necessary for continuous improvement, and it is a key to any big data project.  Embracing issues can be difficult, especially for older, engrained processes, but it is the only way to eliminate them.  It certainly is not the easiest thing to do, and requires a humble mindset entering an improvement project.  Process mining has all the key factors of a successful big data software, and it could be very useful for manufacturers that want to embrace the big data revolution.

 

Do you believe addressing KPIs first is the best way to approach a big data project?

Do you think process mining is actually a new or different type of big data analytics or just a rebranding of basic big data?

Do you think that some manufacturers are reluctant to implement big data projects because they do not want to know their inefficiencies?

 

http://www.mbtmag.com/article/2017/02/why-manufacturers-need-process-mining-new-type-big-data-analytics

Caterpillar is Saving Big Money using Big Data and the IoT

In the article IoT And Big Data At Caterpillar: How Predictive Maintenance Saves Millions Of Dollars, the author examines an interesting case of the company Caterpillar saving significant amounts of money using big data and the IoT.  The best part of this case study is that Caterpillar is seeing a very quick ROI on their big data investment, which is not something that can be said for most companies.  As a Caterpillar manager put it, you don’t have to look for a “grand slam” with big data; sometimes you just need multiple smaller applications of big data to experience significant savings.  In this instance, gathering as much data as possible seems to be the best approach, and utilizing experts in the processes and in the data to analyze and understand the insights gleaned helps realize real value.

Caterpillar utilized big data on in its Marine Division, mainly to analyze fuel consumption for its customers as it most affects the bottom line.  Sensors on the ship monitored everything from generators, engines, GPS, refrigeration, and fuel meters, and Caterpillar utilized Pentaho’s data and analytics platform.  Insights gained have been a correlation between fuel meters and amount of power used by the refrigeration containers, and also that running more generators at lower power instead of maxing out a few was more efficient.  The cost savings here added up to $650,000+/year.  Another insight was to the optimization of a ship’s hull cleaning schedule.  Through the collection of data of cleaned and uncleaned ships, the data showed that cleanings should be performed once every 6 months instead of once every two years.  The savings associated with this optimization was $400,000/ship.

In the grand scheme of big data, predictive maintenance analytics seems to be the most powerful tool consistently being used.  With data being generated just about anywhere you could imagine via the IIoT, understanding trends becomes easier and easier.  Interestingly and contrary to previous articles, Caterpillar believes that you can’t collect too much data.  They point out how data storage is very cheap.  In the words of a Caterpillar manager, you can’t see “relationships about relationships” in the data if you don’t collect it.  Although a more is better approach is definitely not what some companies have ascribed to, it seems to be working well for Caterpillar’s marine division as they continue to pull value of out of big data and analytics.

Quick returns on big data investments seems to be rare, so do you think that companies just aren’t utilizing the big data correctly?

Do you believe in the more is better approach with regard to collecting data?

Do you believe Caterpillar is more likely to invest in big data projects in other parts of their company due to the success in the marine division?

http://www.forbes.com/sites/bernardmarr/2017/02/07/iot-and-big-data-at-caterpillar-how-predictive-maintenance-saves-millions-of-dollars/#3e01059a5a63

Looking for the Signal in the Noise

In the article A Signal in the Noise: How to Best Manage Big Data, the author advocates some ways to improve the use of data for manufacturers as well as his idea for the best way to approach the use of big data analytics and data management.  The author equivocates big data as sometimes “a needle in the haystack” when it comes to finding and using it in the manufacturing environment.  With so much data produced by even small firms, the management, organization, and analyzation of the data can become overwhelming if not impossible.  Industrial Internet of Things-based systems are estimated to create $4 trillion to $11 trillion in new economic value for manufacturers by 2025, according to McKinsey Global Institute.  With such large value to be had, ignoring or underutilizing data could be a catastrophic mistake for manufacturers.

In a study of manufacturers conducted by the MPI Group, 76% of respondents reported plans to increase their use of smart devices in the next two years while 66% plan to increase their investment in IIoT-enabled products over the same time period.  With many firms taking the necessary steps to collect and use data, a strategic approach is necessary.  The author suggests a number of steps to jump-start the transformation to using data analytics.  Recognizing human limits and the burden of isolation is the first suggested step.  Here the author is advocating that firms understand that human teams are just not capable getting the insights that technology is capable of.  The next step is forgetting the traditional supply chain cycle, and embrace the complexity of modern supply chains.  With the IIoT, data can be captured all along the supply chain which can offer useful insights not previously possible.

Finally, the author advocates understanding four different measures before taking on new data management and analytics initiatives.  Find the actual problem, the “signal in the noise” is the first and foremost issue at hand.  Unless there is direction to the project, the project will almost certainly fail.  Next is understanding the business case.  One has to understand the strategic advantage behind any data management implementation.  Lastly, finding where the optimization is most desperately needed and identifying the experts that are best suited to handle the data being generated is key.  Overall, the biggest pitfall in bringing on new technology is the belief that good things will just happen.  An understanding of the problem, the right people, and a tailored process will allow the technology to do the work it is supposed to.

Do you believe that understanding big data is really about finding the proverbial needle in a haystack?

Do you believe the increase in smart device usage automatically translates to more useful big data, or just more data in general?

As with most strategic IT plays, projects start off to gain a strategic advantage but quickly become part of the IT infrastructure.  Do you think we are in the middle stage between big data being a strategic advantage and a necessary IT infrastructure requirement for manufacturers?

 

http://www.industryweek.com/technology/signal-noise-how-best-manage-big-data