5 Manufacturing Trends to Watch in 2019

States News Service

January 18, 2019

The future of the manufacturing industry will be shaped by a number of ever-evolving trends and technologies. While theres no telling exactly how things will play out in the long term, it seems safe to suggest a few will have a profound impact on manufacturers this year. As a result, its critically important for those within the industry to develop a keen sense of what they are, how they will change over time and, most importantly, how they will impact organizations in 2019 and beyond.

With that fact in mind, lets look at five manufacturing trends to watch in the near term:

1. Intelligent manufacturingThe concept of intelligent manufacturing is always changing. But in the simplest sense, it can be defined as a large-scale integration of cutting-edge artificial intelligence and advanced manufacturing technology and processes. Ultimately, intelligent manufacturing serves to help companies optimize organizational systems, improve product quality, increase the efficient allocation of resources and positively impact customer service.

Advancements in digital technology are driving the rise of intelligent manufacturing. Its now possible for integrated systems to enable communication and collaboration between equipment and people, allowing for the creation of customized products to be accomplished with the efficiency of mass production. In doing so, manufacturers can increase customer engagement and positively impact relationships with equipment end users.

In fostering the development of a connected ecosystem of people and equipment communicating in real time, manufacturers are poised to better meet the needs of the industries they serve while simultaneously reducing cost and inefficiencies.

2. Data utilizationBeing able to simply manage the mounds of data generated by manufacturing processes is not enough anymore. Companies need to go beyond efficiently storing information and consider how best to go about using it to gain insights into their businesses and make actionable and informed decisions about their future.

In the most traditional sense, data management consists of harvesting company data, constructing an ecosystem to support it, and then acquiring business intelligence hardware to aid in organizational assessment and analysis. The problem is theres often too much data to manage, so companies fail to consistently make observations or find useful takeaways from the information. In short, theyre not utilizing the data, and theyre not really even managing it, either.

According to a recent article in IndustryWeek, organizations must be willing to ask (and answer) some key questions about how they use data. In doing so, they can begin to identify areas of improvement and ways in which the information can be leveraged to ultimately benefit their bottom lines. Questions include:

  • How do we visualize the information that drives our business?
  • How do we make the right decisions required to grow our business?
  • What are the current sources of data we use to measure, analyze, and sustain a true business reality?
  • Utilizing current sources of data, what areas of rapid improvement will quickly affect changes in our business?
  • What kind of data is available to an individual who understands how to read it?

Organizational data can be overwhelming to manage. But leading companies today are establishing processes and investing in tools to help increase both profits and productivity. And, as technology continue to develop and evolve, opportunities related to data utilization will become more and more prevalent with time.

3. The Internet of Things (IoT)The marriage of networked sensors and intelligent devices with connected equipment on the manufacturing plant floor has been one of the most impactful and transformative trends the industry has seen in quite some time. The ever-developing Internet of Things has not only turned traditional supply chains into interconnected and dynamic systems, it has:

  • Fundamentally change the way in which products are made.
  • Increased organizational efficiency.
  • Improved organizational safety.
  • Reduced organizational costs and complexity.

However, according to a recent article in Wired, where the Internet of Things is poised to make a mark in the not-too-distant future is enterprise business models. More specifically, it could lead to more and more high-value equipment being leased, as opposed to being sold outright. The machinery of the future could be outfitted with built-in sensors and marketed as both a product and as service. As a result, equipment owners would then be able to monitor it remotely and provide maintenance, repairs and necessary upgrades automatically. This would allow end users to focus on the work at hand instead of worrying about the condition of the equipment, leading to increased productivity and satisfaction.

The Internet of Things has already had a profound effect on the manufacturing industry, but it offers the potential to do so much more in the coming years. IoT technology is not only capable of helping manufacturers improve productivity and efficiency, but now can be leveraged to positively customer service and end user relationships.

4. Workforce trainingTheres no overstating the seriousness of the manufacturing industrys skilled worker shortage in 2019. Manufacturing employs roughly 9% of the U.S. workforce, yet it is increasingly unable to fill necessary positions with qualified people. As it stands, there are three times as many open skilled labor positions than are being filled. The skills gap is significant problem right now, and theres no reason to suggest anything will improve in the short term.

Thankfully, efforts are under way to find creative ways to address the skilled worker shortage. According to this article from Foley and Lardner LLP, states such as Michigan and North Carolina are attempting to lead the pack in terms of innovative solutions to the skills gap crisis.

A recently adopted plan in Michigan calls for the investment of $100 million in initiatives that award competency-based certifications, offer aid to schools in changing their curriculum and equipment to help close the skills gap, as well as provide support for career development and school instruction. All of this is being done in an effort to prepare young people to enter the work world prepared for a career in the skilled trades. In addition, North Carolina is currently considering enacting similar legislation to address the skills gap in the state.

By investing in training and education, key stakeholders inside and outside the manufacturing industry can begin to connect with the workforce of tomorrow, inspire them to strongly consider a career as skilled workers and perhaps most importantly develop them into qualified employees.

5. Artificial intelligenceArtificial intelligence is everywhere, so it comes as no surprise that its beginning to be incorporated more and more info manufacturing. In the near future, manufacturing facilities will evolve into connected networks of people and machines with supply chain assets, design teams, production and quality control all integrated into a highly intelligent engine that monitors everything and provides actionable data and insights.

Artificial intelligence can come in many forms, and the industry can expect it to make its presence more and more known in manufacturing facilities as:

  • Virtual reality.
  • Automation.
  • Internet of Things (IoT) infrastructure.
  • Robotics.

While there are concerns about artificial intelligence eventually replacing human workers in a variety of industries, what seems clearat least in the short termis the technology will drive increased efficiency and productivity. By incorporating the technology to help manage operational assets, companies are free to focus their time, effort and resources on product innovation and other key strategic priorities.

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Report: U.S. Food Recalls Increased 10% Over Past 5 Years


January 18, 2019

By Clyde Hughes
The number of food recalls has increased 10% over the past five years, and some happened because of archaic laws, a nonprofit watchdog said in a new report released Thursday.

The report by the U.S. Public Interest Research Group, or PIRG, said recalls from crackers, to lettuce and meat increased from 2013 to 2018. U.S. Department of Agriculture Class 1 recalls of meat and poultry increased by a dramatic 83%.

The Class 1 recalls involve a health hazard situation in which there is a reasonable probability that eating the food will cause health problems or death, the PIRG reported. Those recalls include beef suspected of contamination from E. coli and poultry from salmonella.

The food we nourish our bodies with shouldnt pose a serious health risk, Adam Garber, the consumer watchdog for PIRG, said in a statement. But systemic failures mean were often rolling the dice when we go grocery shopping or eat out. We can prevent serious health risks by using common sense protections from farm to fork.

Two E. coli contaminations in romaine lettuce left five dead and more than 100 hospitalized in 2018 while a salmonella outbreak in raw beef killed 246 as workers discarded 12 million pounds of beef, USA Today reported.

This month, the Centers for Disease Control and Prevention announced that the latest leafy vegetable recall because of E. coli appeared to be over after stating that contaminated lettuce from California that made people sick was no longer in stores and restaurants.

The scare reached into Canada as well, as 29 cases of E. coli linked to romaine lettuce from the same area were confirmed.

In the meat industry, PIRG blamed archaic laws that allow producers to sell meats that test positive for salmonella, saying that some recalls could have been prevented.

These recalls are a warning to everyone that something is rotten in our fields and slaughterhouses, Viveth Karthikeyan, a PIRG consumer watchdog associate, said in a statement. Government agencies need to make sure that the food that reaches peoples mouths wont make them sick.

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Agile Isn’t Out, You Are


January 17, 2019

By Duena Blomstrom

By this time if you work in technology in any capacity its impossible that youre not at least vaguely familiar with Agile as a concept and the fact that it is the cornerstone of the achievements coming out of Silicon Valley.

Sadly, thats also the level most people remain at even when they are meant to be involved in practicing it in their day-to-day lives.

We all love a good buzz-feed-like list of what to do or not to do and Agile offers none of that, so it can be hard to engage at first and frustrating to continue going forward, in particular, if the people employing it have had years of working in a very different fashion.

Whether in project management, software development, marketing, sales or management, having the ability to change the methods you employ while working and adopt an Agile mindset instead is a competitive advantage and allows you to deliver more to the business and do so faster. Who doesnt want to be better?

Trouble is, the part above that says adopt an Agile mindset is not a matter of speech but the actual crux of the issue. It requires a real change of mentality and a high degree of emotional investmentin lieu of mere determinationto employ this practice.

To be or not to be truly agile

Attempting to do what I call Agile by numbers in the sense of adopting whatever process that calls itself Agilebe it Scrum or Lean or Kanban or any of the new trendy executional variations we see every daywithout having any type of personal conviction that it will work, and therefore simply relying on a set of actions is doomed.

The Agile manifesto says it clearly: its all about the people not the process. Despite that, most people that come near it will try to rely on process and overcomplicate the procedure and the terminology because keeping it fundamentally simple is a lot more complicated than it looks and requires a degree of emotional intelligence many people were not called to exercise in their work lives.

What does emotional intelligence have to do with it? Ive often written about this in the past, Agile is a Way of Thinking not a Way of Working. Being Agile creates mental pressure to the practitioner. The old ways of work have served the employee for years, changing anything is intensely risky and most of us are risk averse when it comes to our professional lives. At the same time, anyone who looks under the hood understands that Agile speeds things up but may expose limitations as it needs the practitioner to eternally be alert, always question their progress, never stop pushing themselves and others and always strive for new and better.

Excellence is not comfortable or easy to attain and all that Agile does is enable excellence.

Clearly, this amount of emotional intelligence and high performance is possible as some people and some enterprisesfew and far betweenhave managed to embrace Agile indeed not just pay it lip service.

Sometimes it took the professional to have arrived at Agile on their ownwhether by reading the wonders of delivery it performs for Google or Amazon or by employing some of it in their own lives before they could see it part of their work. Sometimes, while it may have been mandated and made obligatory from the top, they have had the right Agile coach that knew how to instill a love of the concept and they have learned to appreciate its merits and have truly taken it to heart.

And it takes taking it to heart. I often say Agile is a religion for the pleasure of watching the uncomfortable shifts in my dialogue partner and while said for drama effect, it isnt untrueto be truly agile you have to be willing to believe. Thankfully that belief doesnt have to be in any invisible entity but in clear statistics and hard-to-argue-with solid results showing how much more innovative, efficient and successful organizations that truly are Agile can be.

For the younger generation that is simply now coming into the workforce, things are somewhat easier as they dont need to make a painful moral transition between waterfall ways of working and Agile, they simply know there is this magical way that the digitally native technology giants and other nimble entities are using with excellent results, and they can embrace it right away. No questions, no mourning over Prince certifications.

Lets wait agile out, its a phase

For the rest of us who have been used to a different order of things its not as easy. Which explains why, set to the background of the initial founders and the early evangelists becoming more and more demoralized, and the concept gaining more and more momentum as the cornerstone of the new ways of work, there is a reactionary meh, Agile is just a trendy concept, we dont need to use it vibe coming from some players. Wishful thinking of the worst kind and also a harmful stance subconsciously designed to give excuses to the incapable.

Agile is not going anywhere. While it will be slower to penetrate some functions of the organization and even extend itself to social interactions and education, it will undoubtedly do so in the future and next generations will know no other way of thinking than flexible, collaborative and effective.

Once every organization accepts that, they can move on to figuring out how they can truly get their people to take it to heart which wont be easy.

Hire and fire for an agile heart

Two of my practical suggestions are avoiding the common pitfalls of doing Agile wrong as they relate to process, and ensuring that your own leaders are Agile.

Ive said this many times before, but there is no hope for the organization that claims they will embrace Agile while their own leaders havent done so.

As a matter of fact, if youre a company who is serious about progress, the most sensible thing to do, is only hire senior management that is demonstrably Agile, who live and breathe it themselves in their work practice and their day-to-day life alike.

That and fire the ones that arent Agile. Every last one of them. Set them free to find the last bastions where win is not on the In Process column and once you do, go back to moving become a truly Agile organization to the Done list.

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Harnessing Multiple Data Streams and Artificial Intelligence to Better Predict Flu

Indian Health Care News

January 17, 2019

Influenza is highly contagious and easily spreads as people move about and travel, making tracking and forecasting flu activity a challenge. While the CDC continuously monitors patient visits for flu-like illness in the U.S., this information can lag up to two weeks behind real time. A new study, led by the Computational Health Informatics Program (CHIP) at Boston Childrens Hospital, combines two forecasting methods with machine learning (artificial intelligence) to estimate local flu activity. Results are published today in Nature Communications.

When the approach, called ARGONet, was applied to flu seasons from September 2014 to May 2017, it made more accurate predictions than the teams earlier high-performing forecasting approach, ARGO, in more than 75% of the states studied. This suggests that ARGONet produces the most accurate estimates of influenza activity available to date, a week ahead of traditional healthcare-based reports, at the state level across the U.S.

Timely and reliable methodologies for tracking influenza activity across locations can help public health officials mitigate epidemic outbreaks and may improve communication with the public to raise awareness of potential risks, says Mauricio Santillana, PhD, a CHIP faculty member and the papers senior author.

Learning about localized flu patterns

The ARGONet approach uses machine learning and two robust flu detection models. The first model, ARGO (AutoRegression with General Online information), leverages information from electronic health records, flu-related Google searches and historical flu activity in a given location. In the study, ARGO alone outperformed Google Flu Trends, the previous forecasting system that operated from 2008 to 2015.

To improve accuracy, ARGONet adds a second model, which draws on spatial-temporal patterns of flu spread in neighboring areas. It exploits the fact that the presence of flu in nearby locations may increase the risk of experiencing a disease outbreak at a given location, explains Santillana, who is also an assistant professor at Harvard Medical School.

The machine learning system was trained by feeding it flu predictions from both models as well as actual flu data, helping to reduce errors in the predictions. The system continuously evaluates the predictive power of each independent method and recalibrates how this information should be used to produce improved flu estimates, says Santillana.

Precision public health

The investigators believe their approach will set a foundation for precision public health in infectious diseases.

We think our models will become more accurate over time as more online search volumes are collected and as more healthcare providers incorporate cloud-based electronic health records, says Fred Lu, a CHIP investigator and first author on the paper.

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