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Tech

Originated in Germany, Industry 4.0 translates as “a holistic automation, business information, and manufacturing execution architecture to improve industry with the integration of all aspects of production and commerce across company boundaries for greater efficiency”, according to Automation ISA.

From this starting point, the source article delves into the history of Industry 4.0 initiative. The Industry 4.0 initiative is part of a 10-point high-tech German strategic plan, created in 2006 and continued in 2010 by introducing the High-Tech Strategy 2020. Science and industry need to cooperate, in order to turn knowledge into skills.

Creating networks that incorporate the entire manufacturing process and convert factories into smart environments involves linkages. Linkages such as “smart machines, warehousing systems, and production facilities that feature end-to-end integration, including inbound logistic, production, marketing, outbound logistics, and service”.

Real-time data, a key element in the Industry 4.0 chain of operations

Real-time information enables strong decisions, based on insights. When it comes to production, it enables a superior reactivity and responsiveness in what production chain materials and operations are concerned.

Also, Industry 4.0 is based on asynchronous manufacturing.  This requires that the components in the production flow are able to use “auto identification technology to inform each machine and operator what needs to be done to produce the customized end product at each step of the production process.”

Based on real-time field data, the machines can be rapidly configured so they would adapt to customer specifications and other commands inherent to the production operations.

The collected data also serves as prime material for a range of analytics. These provide a bonus post real-time advantage to those in charge. By analyzing the data, such systems provide recommendations on improving performance and productivity.

Using embedded intelligence at all levels, the advanced cyber-physical systems (CPS) save “significant cost, providing greater flexibility and improved reliability.”

What binds together this new, developing industrial landscape is a series of software solutions that allow for the data to be collected and processed. Furthermore, the insights become recommendations. The decisions then turn into commands that go back into the cycle, driving modified, optimized operations.

 

Standards emerge, as well as a worldwide agenda

With separate, but similar Industry 4.0 agendas in countries such as Germany, China, Japan and/or others, a sum of specific standards emerge. These standards require harmonization, if they are going to work seamlessly at a global level, regardless of the physical area where the industrial processes involved take place.

Future automation systems must adopt open source multivendor interoperability software application and communication standards similar to those that exist for computers, the Internet, and cell phones. Industry 4.0 demonstrations acknowledge this by leveraging existing standards, including the ISA-88 batch standards, ISA95 enterprise-control systems integration standards, OPC UA, IEC 6-1131-3, and PLCopen.

Process automation is at the core of this plan. It becomes more and more present with each industry entity that joins this trend. The Industry 4.0 vision of the future factory joins together advanced technology hardware and brilliant software solutions, for a flawless functionality.

We are getting there with each software solution. Producers can unload more and more of their operations onto the digital, be it monitoring operations, management, coordination or others.

Call us for software solutions partnerships – we build the software you need for going one step further into the Industry 4.0!

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Tech

The vulnerability of Industrial Control Systems (ICS) systems is a major concern both for their beneficiaries, as well as for all those involved in the development of such software solutions. While software engineers (in and beyond ICS), know that a solid software architecture and reliable coding are the only way to go to reduce cyber risks, the users sometimes neglect the best practices in the daily use of software solutions.  When steering away from code that ends up being vulnerable, or easy to control via data breaches, as well as from its faulty deployment or configuration, the ICS-based recommendation can do no harm. They are also useful when considering other types of software solutions.

We browsed a few recommended methods for developing strong and reliable ICS software solutions, on the users’ side.

The ICS system environment induces an urgent need to solve or avoid vulnerabilities. This urgency drives best practices in this line of work. By extension, any solution with implications or application in the IoT field can be approached in the same way, even if the effects of its potential vulnerabilities are sometimes more difficult to grasp. But any element in an interconnected system is essential because the system is as protected as its weakest element is.

 

A seven steps list to avoid cyber risks, from Automation World

The list comes from a supplier of industrial cybersecurity software and services. It’s meant to provide a solid grounding for all the types of professionals who are involved in building and delivering safe and secure ICS software solutions.

 

As the author mentions, the list summarizes the “core steps every industrial company should take to secure their control systems at the most basic level”

Design your network with cyber security in mind

  • The software solutions beneficiaries/users should secure their networks to avoid exposure

Monitor your deployed software

  • Make sure you notice events and any abnormal behavior before it’s too late

Keep a tight inventory of all devices connected to your network

  • “From controllers to human-machine interfaces (HMIs) to engineering workstations, all assets on your network should be accurately inventoried so there aren’t any unknown devices, thereby enabling rogue assets to be quickly identified”.

Manage your logs, to understand the behavior of all involved devices

  • You can optimize performance once you have the complete image

Manage the configurations of all involved devices

Use industrial firewalls

Institute privilege control

 

As a user of software solutions, do these recommendations sound familiar?

Avoiding cyber risks is a common effort. Good software engineers strive to build and deliver the best, most secure products. Vigilant users should join in by materializing best practices, such as those mentioned above.

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News

This week we focused on autonomous vehicles, inspired by this Innovation Enterprise post that targets the decisional factors inside organizations. All those concerned need to prepare in advance for the incoming changes that are set to affect industry after industry. Just to have an idea about the scale of the disruptions, their certainty and their character, let’s go through this topic, the way the mentioned publication approached it.

Autonomous vehicles will pervade the logistics and transportation fields, and the legal adjustments point to this

Firstly, we should notice that the article looks at the way autonomous vehicles progress in the US environment. Therefore the presented implications and legal changes are in relation with this geographical area, for now.

The Department of Transportation recently issued a new guidelines document of 70 pages. The officials stated that they changed the definition of “operator” and “driver”, to allow for AI-driven vehicles.

Based on this major change, those in charge of businesses in which such vehicles might play a role in the future should prepare in advance. Exactly how will autonomous vehicles impact such businesses? Advice for determining the future impact of the changes to come is included in the article.

Mapping out what companies will drive this type of change is yet another step in the process of getting ready for it. Autonomous vehicles come with AI (Artificial Intelligence). Companies such as Google, Tesla, or even Dominos Pizza made no secret out of their AI commitment.

Besides keeping an eye for the moves of such innovators/adopters, investing in stocks related to AI is a second option many will consider.

 

Going fully driverless means high technology and overcoming any security issues in autonomous vehicles

Analysts have estimated that going fully driverless is an option that could become real in transportation around 2030 or half 2040s. We are talking trucks and goods delivery, and the figures already point out considerable cost saving benefits and not only.

The road to this stage may seem long and surely it’s a winding one. However, the first official and regulatory step may well be the new definition of what a driver is.

On the other side, road safety and cyber security concerns show the need for high-performance, fault proof software and hardware. Those solutions that guarantee the safety of all those taking part in traffic are the only way to move forward.

Going fully driverless in transportation and delivery does not yet have consumer acceptance. Autonomous vehicles still have some way to go until convincing the majority of people they are in no way a risk on the road. In any case, they still have to prove not being a bigger risk than the vehicles with human drivers.

Autonomous trucks generally officially operate at what’s known as Level 2, an engineering standard that includes technologies such as automatic braking, acceleration, and some amount of steering. (Basic cruise control, by contrast, would amounts to Level 0, and certain features such as lane-assist or adaptive cruise control would be Level 1). However, autonomous trucks are often effectively operating at Level 4 – or “high automation,” with their safety drivers generally only taking over on local roads.
– Richard Bishop, an automated vehicles industry analyst, quoted by US News

Image credit: curbed.com

 

 

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Tech

City planners and technologists joined forces at Smart Cities Week 2018 in an exercise of simulation for businesses. The theme was the future the smart city, which is not at all far-fetched. All around the globe initiatives for intelligent, connected IoT-based urban centers are in various stages of development.

To understand the full scale of requirements, challenges and multiple tasks involved by such a mega structure, we browsed a recap of the simulation, as featured on IoT for All.

 

Things to expect when involved in a smart city project

Although the increased specialization in the technical field over the years may not equally put all participants in a project in a similar strategic posture, certain major challenges are bound to affect all. Even if layered in complementary projects, micro projects and various team types, the professionals who are part of the overall team do have to acknowledge the bigger picture.

What would a few of the common challenges might be? Lateral thinking is one of them. For the success of such a venture, those who make decisions, as well as those who decide for their own subsidiary area of responsibility need to bring an indirect and creative approach to the table.

Balancing the budget against what are indeed the much needed strategic investments is yet another must. Investing in new technologies blends together with retrofitting older structures. However, blending means seamless integration. The participants need to think things through. They also need to have a can do attitude, to grasp the big picture, as well as be quickly aware of the possible pressure or blockage points.

 

A process of bartering and flexible adaptation

The simulation in cause was extremely interesting due to the fact that it reunited city planners with the specialist in technology.  While the professionals in urban planning brought an approach forged during the specifics of their everyday activity, some of the technologists had their first opportunity to see how and why this type of project is different.

City planners are often reluctant to changes, stick by their budgets and need to understand the technology and translate it into financial lines. Understanding the technology alone took a while for some of the participants. The technologists had to meet them halfway in relation with certain issues.

Collaboration and strategy are key on the road to a functional smart city – as the author repeatedly underlines it. The aim and the measurement elements is the citizen quality of life – a notion that seems at hand, but needs defining. It also requires a sustained activity on the line of planning, so it would indeed materialize into better services, better living conditions and so on.

 

Keywords for activities related to the smart cities of the future

We selected a few keywords that might not be the first things that come to mind when contemplating the idea of smart city:

  • Multiple stakeholders
  • Constrained budgets
  • Challenging social dynamics

Other keywords are less surprising:

  • Economic growth
  • Intuitive infrastructure
  • Public-Private Partnerships
  • Collaborative processes

Materializing smart city projects may involve a sum of integrations. Some software solution can be adopted into such a project, while they previously existed in the private environment. Others can regard custom-made software programs and applications.

Whatever the case, having the right partner in software engineering is of great use. Our company is an example of such a partner – with the experience accumulated in our projects along the years, we can tackle IoT and mobile challenges related to the major ventures of the future.

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Leadership

ZDNet takes a look at the AI and Machine Learning predictions, in what the business environment is concerned. Expected to surge in 2019, the rapid adoption of these new technologies also brings different business challenges.

The article mentions the necessary (and huge) shift that is absolutely required for organizations to thrive. Going from buying “black boxes that will fix our problems and offer us solutions” – as the publication puts it, to the next stage, won’t be easy.

A passive attitude welcomes possible cases of “algorithm sprawl, project management issues, and vendor hype”.

But what modern, wise organizations do? How can we all avoid the so-called bad implementations of AI & ML?

 

 

Who will have to handle AI data?

Since data science is not a magic  trick – although sometimes it may seem so – in order for it to work, key people in your company come in. Apparently, “everyone from mid-level managers to C-level execs are going to use this AI”. They also need to understand how to use it, to be prepared and aware of this new age of technology.

Therefore, determining who will work with your AI data is absolutely necessary. You need the big picture before going into details. However, getting the right big picture requires experience.

Use experts – get consultancy as an ally in this big battle. You want to understand what will be going on, and someone who can put the process into perspective can make you go a long way. Having worked with systems, apps, connected data, Artificial Intelligence and data science, professional consultants can provide a reliable blueprint. How will it work for my business? The answer to this is much more accurate when you obtain it with the right guidance and assistance.

 

What does your AI data need to provide answers for?

As the article we’ve mentioned lists, operating Big Data generates effects that go beyond the lucrative insights.

You will also need to have a strategy and to deliver reports to your board.

As the process evolves at a global level, you will need to choose the most suited AI services pack – from the big tech cloud providers.

Data scientists are still scarce, and the models you will be dealing with lack transparency.

The AI-trained professionals are also scarce, and this specialization just made its way into the academic curriculum. For now, hands-on experience prevails.

Your AI data needs to provide answers and guidelines for all of the above, and more. You will be working with a tool with huge potential that you barely understand. Nevertheless, you need to move relatively fast while making the best choices. The AI tools unleash their potential on the go. Add an extra layer of software solutions – and you have a new functionality. Get on board with the best cloud provider, and you will be able to deploy your tools next-level style.

 

Prepare for the next step, by getting a partner that understands the new technology

It’s not only AI. As we’ve seen, it’s also Machine Learning, Big Data, algorithms, analytics, IoT, embedded sensor software, various layers that have to integrate with each other.

Working all these out into the strategy of your company, while resetting certain functionalities and expanding others – this won’t be easy.

As all things good and new, as overwhelming as it may seem, it needs to be done. The sooner, the better. Make the first step and choose a reliable software partner, one experienced in business digital transformation. Call, talk, schedule the meetings you need, soon you will have a whole new perspective on the matter.

 

We are here for you – our know-how and experience are both rich, and our eagerness and innovative spirit are the right match for this future of technology.

Contact us and let’s find out more about how a potential partnership may look like, and what it can do for both of us!

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