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What Makes Smart Factories “Smart”?

What Makes Smart Factories “Smart”?

The fourth industrial revolution, also known as Industry 4.0, is sweeping across Asia Pacific with more manufacturers building smart factories. Nearly half of manufacturers in Asia Pacific will have fully connected factories by 2022, serving customers with shorter timelines and higher quality standards. This dynamic shift towards smarter factories has prompted companies to focus on technologies which deliver greater efficiencies and reduced operational costs. By Damien Dhellemmes, Country President, Singapore, Schneider Electric

Maximising Smart Factories

Damien Dhellemmes

Companies in the region are equipping themselves with solutions such as the Internet of Things (IoT), cloud, big data, and analytics to help drive operational excellence across the enterprise.

In the automotive industry, for example, solutions such as predictive analytics are being implemented to help companies reduce unscheduled downtime and maintenance costs. Predictive analytics can be used to forecast and diagnose problems several days or months before they occur, using advanced pattern recognition and machine learning.

Compared to older factories, maintenance in smart factories has now become a proactive strategy rather than a reactive process. Employees now increasingly play a greater role in the planning and decision-making process in the plant.

Working Smart

Industrial Internet of Things (IIoT) presents manufacturers with an opportunity to improve the connectivity of their plant facilities and empower workers to be “smarter”. Smart and connected devices can be used to link existing manufacturing solutions to drive improvements at a unit level. Internal quality checks for plant equipment can also be made by employees in real-time. This means employees can operate remotely with better visibility of plant operations without having to be on-site.

Companies can enable advanced workflow software allowing employees to focus their energy on their work, creating new opportunities for the business rather than spending time on repeated tasks. Automated workflows mean that employees can manage their work with little to no oversight. By streamlining processes and workflows, companies can manage their routine processes consistently and efficiently with no human error.

Leveraging Data

Smart workers for smart factories | Image Source: Schneider Electric

One way to maximise efficiency and improving collaboration amongst employees is with mobile workforce management solutions. Such solutions collect data from stranded assets that are not digitally integrated to the plant. This means that best practices can be adopted across the plant by standardising, documenting and enforcing maintenance inspections and procedures. This results in increased accuracy of executed tasks and asset performance optimisation.

With mobile access capabilities in the plant, employees involved in key decision-making process can be granted access to relevant data when needed. Providing access to data empowers them to be more active participants, making more informed decisions during the work process. The overall productivity and efficiency of the workplace is improved using actionable insights derived from the data using mobile access.

Drive Digital Transformation To Stay Ahead Of The Game

With actionable insights, employees are empowered to make better decisions in the workplace

We ourselves strongly believe in the value of smart factories. We ensure that our own factories (more than 170 worldwide) integrate latest technologies to become pilots for new industry 4.0 solutions. For instance, our factories in Batam have become a test bay for machine learning, AI, predictive and digital maintenance, connected machines and processes. This has allowed us to increase the performance of our operations, while strengthening the link between our research and development teams and operations.

The integration of big data, cloud and IoT capabilities will pave the way for companies to work towards their smart factory vision, becoming more energy efficient and sustainable in the long term. It is key to align mid to long term strategic goals with the digital transformation infrastructure of the business before embarking on the digitalisation journey. Companies need a digital strategy in place to carefully assess the organisation’s needs, before analysing whether digital solutions are able to deliver operational excellence across the value chain.

At the same time, smart factories need smart workers. Companies need to go beyond digitising their plant operations and invest in their talent to drive digital transformation of the business. When employees are upskilled, companies can fully leverage the benefits of their smart factories.

Optimising IIoT Time To Value With IT-OT Alignment In Manufacturing

Optimising IIoT Time To Value With IT-OT Alignment In Manufacturing

There is a popular saying that “if you want to go quickly, go alone, but if you want to go far, go together”. These wise words are particularly applicable in manufacturing, where effective production requires the precise coordination of a variety of moving parts. Contributed by Bsquare Corporation

Historically speaking, though, this mantra has not extended across the full breadth of industrial operations. In particular, information technology (IT) and operational technology (OT) teams have traditionally worked largely independently of one another–though exceptions do exist.

Now, technological advances are disrupting the status quo. The rise of connected factories and digital transformation initiatives–specifically Industrial Internet of Things (IIoT) projects–is forcing manufacturers to rethink conventional, siloed operations. Thanks to IIoT, operational data is more accessible than ever, presenting a massive potential value in the form of opportunities for businesses to gain unprecedented clarity into operations to enhance decision-making, efficiency, and performance. Amplified by intense competition and the harsh realities of economic and regulatory demands, the allure of these benefits is driving IIoT spending to an estimated US$189 billion in 2018 as manufacturers search for an edge.

But it is not as simple as just installing equipment sensors and upgrading software. Effectively deploying IIoT in an industrial environment is a very complex undertaking that requires a careful, strategic approach. And even then, there is intense pressure to demonstrate return on investment (ROI) in short order and continue scaling across operations to maintain a competitive edge. Achieving maximum benefit in the least amount of time takes coordination and cooperation across multiple departments, and bringing IT and OT together is a critical step.

While there are both historical and current examples of successful cross-functional collaboration, aligning these two inherently different organisations is no easy task. Issues around who is responsible for what, unfamiliarity with how each other work, and lack of system organisation were also popular responses.

Enabling IT-OT For Your Business   

Differing missions, priorities, culture, philosophies, education, and background are just a few of the factors shaping the contrasting world views that drive a wedge between these two organisations. Furthermore, intangibles can vary greatly from one company to the next, so there is no uniform guidebook for this relationship. That said, obvious differences in hardware, software, and operating environments provide further context for this departmental divide.

In addition to expected technological differences between companies, the perception of IT’s role and responsibilities can differ across a manufacturing organisation. Typical duties include supporting business and administrative functions and providing network access and connectivity. Their focus on a digital environment makes things like data processing speed, system reliability and security, primary concerns. As such, IT has had to embrace rapid innovation and change to keep pace with developing technology.

Focusing on production environments and interactions in the physical world often ties OT activities directly to the bottom line of the company. Reliability and longevity of business-critical assets are primary concerns, especially since output goals are often on the line. Equipment can cost hundreds of thousands of dollars and, in some cases, operate virtually non-stop, in harsh conditions, spread over great distances for decades at a time.

Additionally, automation and control systems tend to operate in isolation and correspond to a single specific machine and/or manufacturer. Maintaining long-term stability over a widely dispersed asset population running on a combination of unique or custom systems has made OT more resistant to change, and late technology adopters.

Proactive Approach To IT-OT Alignment

Nonetheless, collaboration is not unprecedented. A host of manufacturers have initiated intermittent projects that blurred the IT-OT lines throughout the years. Initiatives generally centred around adapting elements of IT for more industrial environments—such as Ethernet networking and programmable logic controllers (PLCs)—and addressing security issues. These pioneering efforts provide a hint of what cooperation can achieve, paving the way for subsequent joint ventures that are becoming progressively commonplace as technological advancement has accelerated.

The permeation of “smart” equipment has also led some manufacturers to build technology support units within the OT organisation to carry out IT functions. This approach is effective on the department level in terms of facilitating technology upgrades and can help bridge the culture divide by introducing some of the IT point of view into OT. However, it is inefficient on a company-wide level as it requires redundant personnel and resources, making large-scale implementations cumbersome.

The common thread of IT-OT interactions to this point is that each was born out of necessity. But now, to effectively seize the new opportunities advancing technologies present, manufacturers must take the next step. Adopting a proactive approach to IT-OT alignment makes it possible to unlock the full potential of IIoT– helping industrial businesses stay ahead of the curve, avoid technology-enabled disruption, and gain a competitive advantage.

IT-OT Convergence

Though it is been around in some form for years, the proliferation of machine connectivity has shifted into overdrive–steadily infusing OT with elements of IT. These increasingly digital assets set the stage for IIoT to provide access to previously unavailable data. But deploying new technology is only part of the equation.

True digital transformation begins once an IIoT initiative has achieved strategic importance company-wide. It is at this point that companies recognise the need to look beyond old ways of running a business and rethink conventional corporate structures. This realisation enables deeper exploration into new avenues for taking advantage of data coming from operational equipment in concert with other data sources and business systems to fully assess what is possible.

For instance, instead of focusing solely on monitoring and watching individual machines, the OT team can look at opportunities to partner with IT—along with other stakeholders—to collect and analyse data from all connected operational equipment. Such cross-functional efforts are a major step in giving companies a more holistic perspective to help identify inefficiencies and achieve objectives that can maximise ROI, like reducing downtime-producing failures, optimising performance, and promoting longevity.

Overcoming IT-OT Obstacles

There are a variety of technological obstacles to overcome to bring IT and OT together, and a quick online search will turn up volumes detailing those challenges as well as how to conquer them. However, the organisational aspect of IT-OT alignment receives far less attention, even though the structure of this working relationship is equally vital to IIoT success.

Working extensively with industrial companies provides exposure to manufacturing environments across the spectrum of IT-OT maturity. It is not uncommon to find a variety of teams toiling away on disjointed, small-scale technology initiatives. Although these may fit into the overall IIoT category, they may not be recognised as IIoT projects. With minimal communication across departments, it can take work to even identify how many of these siloed skunkworks efforts are even in progress.

A company’s level of IT-OT alignment, as well as overall IIoT strategy, is generally readily apparent very early on. And it can run the gamut from initial exploratory phase to issuing a request for proposal tied to strategic business metrics. However, while the latter will typically see value on a shorter timeline, manufacturers at any stage of IT-OT maturity can achieve ROI with the right strategy, support, personnel, and partners.

A Key Component Is Leadership

In general, IT-OT disconnects and the lack of a dedicated leadership structure go hand-in-hand. Even so, companies still recognise how valuable data is becoming. So, left to their own devices, various business units and operations teams end up tackling a surprising number of individual IIoT projects, usually focused on solving specific, small problems.

For example, IT may be prototyping a system of sensors and software to help track and manage computer and networking equipment inventory, or a system to push software updates to mobile devices. At the same time, OT may be focused on a system that generates alerts for a piece of mission-critical factory equipment to notify plant managers if something happens that will negatively impact production.

More often than not, these siloed skunkworks efforts end up on the scrap heap due to lack of scalability or objectives that do nott align with organisational priorities. And those that do survive can limp along for years in relative obscurity without generating tangible ROI. Neither is a particularly desirable result. That said, manufacturers do not have to blindly accept this fate, but avoiding it takes work. First, trying to identify these little unsanctioned projects can turn into a lengthy scavenger hunt. Then comes the exercise of figuring out a way to legitimise them, procuring the necessary funding, and securing the support they need to become a strategic part of the business.

When analysing the performance of different manufacturer’s IIoT initiative, the companies that typically succeed on the most efficient timelines are the ones that establish a cross-functional team that represents all stakeholders at the outset. This oversight organisation could take many forms–such as a steering committee, centre of excellence, digital transformation unit, or digital innovation centre.

How To Succeed With IT-OT Convergence

Here are steps manufacturers are taking to maximise IIoT ROI through IT-OT alignment:

Secure management buy-in. One of the most important elements in successfully bringing IT and OT together, and the success of any broad-scale IIoT initiative by extension, is buy-in and support from upper management. IIoT must be considered a strategic initiative from the top down in order to ensure collaboration across functional and territorial boundaries. Management must make it clear that the effort is good for the company and as such, requires agreement among the various stakeholders to work together on execution.

Create an organisation responsible for IIoT. Of the numerous companies, across a spectrum of industries, investing in IIoT solutions, a typical hallmark of the most successful is the presence of well-defined overlay organisations. Viewing IIoT initiatives—and IT-OT alignment by extension—as ongoing is a key factor, as constant monitoring, maintenance, and innovation are necessary to ensure a deployment evolves to continuously meet the internal and external demands facing manufacturers.

Steering committees with cross-functional representatives or dedicated centres of excellence-type organisations are best suited to take on the task of understanding the challenges likely to arise, looking for operational efficiencies between groups, and evaluating standards and technology options in concert with any systems and solutions already in place. Some companies have even created entirely new management positions, such as chief digital officer. Regardless of the details, it is important to treat the initiative as its own entity and not simply an offshoot of an existing cost centre.

Establish clear strategic goals. Once management support and team leadership are in place, clearly defining the strategic goals driving the initiative is an essential step. This is a good time to brainstorm all possible opportunities, thinking outside the four walls of the business to consider how the IIoT initiative might integrate with others in the supply chain. Starting from raw material acquisition to post-sale customer relationships, examine supply chain implications, partners, or any other element that intersects any point along the chain.

Develop a data management plan. Planning for data management needs up front is a must. One of the benefits of IIoT is that it provides the ability to set policies, partitions, and different views of data. Companies can establish data sharing controls to dictate which information becomes public, without compromising the privacy of sensitive material.

Enlist stakeholder participation. As these elements come together, bringing in stakeholders from across the company will become necessary. Representatives from departments such as legal, marketing, and support and repair organisations can help guide privacy policies and enhance insight into the company’s new strategies and potential business models.

Ongoing IT-OT collaboration is key to success with IIoT as part of a digital transformation or Industry 4.0 initiative. With organisational and leadership unity, IIoT technology has nearly limitless opportunity to improve business outcomes and expand the potential for new revenue streams far into the future.

Machine Vision: An Essential Element In An Industry 4.0 Environment

Machine Vision: An Essential Element In An Industry 4.0 Environment

The burgeoning presence of Industry 4.0 is transforming the manufacturing environment. By Wayne Goh, head of ASEAN, Cognex Corporation

One of the most discussed topics in the manufacturing sector today, and a key pillar of Singapore’s smart nation agenda in increasing business productivity, is Industry 4.0—a broadly defined group of emerging technologies that, in tandem, are creating connected manufacturing ecosystems that will bolster productivity, enhance flexibility, decrease operating costs, and deliver invaluable advantages on factory floors.

The term “4.0” originates from the three prior “industrial revolutions”—mechanisation, electrification, and digitisation. Industry 4.0 is associated with a profound increase in connectivity and automation, through the adoption of smart equipment and systems which integrate computing, networking and physical processes, allowing devices and equipment to autonomously exchange information, and control and interact with each other more independently.

While there currently exist many misconceptions and differing responses toward Industry 4.0—from indifference, to adoption, to innovation—the revolution brings with it many opportunities for producers and distributors.

Singapore’s efforts to future-proof its economy has seen the smart nation agenda feature prominently in the country’s precision engineering Industry Transformation Map (ITM), with the acceleration of innovation, development, and adoption of market-ready solutions across factory floors to pave the way for digital manufacturing.

A (Machine) Vision For The Future

One new, key area of growth earmarked in the ITM is the segment of optics and lasers, said Minister S Iswaran, Minister for Trade and Industry Singapore, at the launch of Meiban iSmart Factory in the country. The segment is expected to grow rapidly at an average rate of around 10 percent or more with the new demand for their applications, he added.

To encourage small medium enterprises to adopt new technologies, the Singapore-based Agency for Science, Technology and Research (A*STAR) will also be setting up two model factories slated to be operational by the end of the year. This will allow companies to experiment with advanced technology, with specific focus on manufacturing technology, explained Minister S Iswaran.

Machine vision is an essential element of the Industry 4.0—no other single aspect of the production line captures more information, and can be more valuable in assessing products, finding defects, and collecting data to direct operations and optimise the productivity of robots and other complementary equipment. Unlike simple sensors, vision sensors generate large amounts of image data, intensifying their utility.

The crucial role of vision equipment will increase exponentially in an Industry 4.0 environment. As data analytics capabilities progress, the huge volumes of data accessible through vision equipment can be intelligently and strategically leveraged to a far greater degree. Not only will it be used to effectively identify and flag defective products, but also to understand the reasons for the deficiencies and allow fast and effective intervention.

Ultimately, as Industry 4.0 progresses, this information can be fed to different machines and equipment in the production ecosystem independently, so that enhancements can be made instantly and automatically. These insights could also be shared with similar production lines through cloud platforms.

Speaking The Same Language

With the countless benefits to be realised, it seems likely that manufacturers around the world will demand more of their suppliers to increase investment and usher the Industry 4.0 revolution into their factories. However, capitalising on these opportunities and experiencing the advantages of Industry 4.0 may be easier said than done.

Currently, the typical manufacturing plant environment might be a mélange of incompatible communications protocols—many invented, originated or championed by individual manufacturers—that hamper the easy delivery and exchange of vital data. To realise the full potential of Industry 4.0, instant, automatic, universal communications protocols must be established across different machines and locations. However, given the countless well-entrenched, often competing protocols that now exist, we could easily experience a supplier stalemate in this regard.

Even with the selection of a common technology stack for Industry 4.0 implementation, the large amount of data generated by vision systems means that there still exists challenges in integrating machine vision into Industry 4.0 architecture. At the same time, complementary protocols—while working towards the same objective—are also are making it difficult for a single, all-encompassing global standard to emerge.

Potential, Opportunity, And Challenge In Industry 4.0

The implementation and expansion of Industry 4.0 has created both challenges and opportunities for machine vision suppliers. The exponentially greater value that can be obtained from the information collected and disseminated by machine vision systems can be expected to accelerate their proliferation in a wide range of new applications up and down the supply chain, in the operations of both existing and new vision users.

While the power and promise of Industry 4.0 is still unfolding and evolving, it is imperative that business leaders, industry committees, and decision makers understand the implications of the fourth industrial revolution, and be open and ready to adapt their current, often deep-rooted processes and protocols to make the ecosystem work. Only then can the sector, as a whole, reap the benefits of these technologies to the fullest.

Industry 4.0: Opportunities For Small And Medium-Sized Enterprises

Industry 4.0: Opportunities for Small and Medium-Sized Enterprises

Industry 4.0 is changing the manufacturing landscape and providing more opportunities for SMEs. Contributed by Faro

“Industry 4.0”, “cyber-physical systems” or the “Internet of Things”: the paradigm shift in the production economy is cheerfully progressing under various names. What they all refer to is the digitalisation and networking of production processes and environments.

The idea is by no means new. The difference is that there are now technologies that offer a level of precision, speed and flexibility to a previously unknown degree. In large companies within the automotive industry, these processes are already offering enormous efficiency and diversity. These companies will set the pace for numerous supplier industries and thus take “Industry 4.0” to small and medium-sized businesses. It is precisely here that the attractive potential for value generation needs to be made visible and concerns and fears assuaged.

Industrial Evolution

One important aspect is that although we may always refer to an “industrial revolution”, Industry 4.0 is far more about an industrial “evolution” that demands tailor-made solutions. Production measuring technology and sensor technology are key tools on this path.

Global megatrends such as resource efficiency, mastering new process technologies, greater flexibility and transparency exert a strong influence on the production industry. The requirements and customer preferences that companies must address are growing: diversity, personalisation of products, correspondingly small batch sizes or the desire for seamless documentation. These issues require answers if a company is to be successful in the market and remain competitive in the location over the long term.

Large companies that have consistently invested in the automation of their production processes can now expect optimised machine capacity utilisation, rapid production times and a lower number of rejects. They are able to react promptly to changes in the market and to produce small product series at low cost.

Intelligent System Networking

This is made possible by the intelligent networking of systems, starting with order management and the material administration and on to the management of the production machines and automated control and quality assurance.

Production or measurement technology plays an essential role here. It provides the high-precision data that the intelligent factory requires. Whether it is the position, the surface properties or the integrity of production pieces, through recognition by means of intelligent measuring systems, data can be gathered and numerous subordinate processes triggered.

For example, product patterns in the production process ensure that the subtle wear and tear of tools can be identified early on with the help of measuring instruments. With a system of “predictive maintenance”, counter-measures can be taken automatically in due time. This makes savings on raw materials, reduces rejects, cuts maintenance and service costs and optimises lead times.

If all information flows are connected optimally with one another then the production process is launched in the system as soon as the order arrives. This steers and optimises the complete process chain automatically, from material flow to the ordering of individual parts and on to the packing and dispatch.

Ultimately, it is the workpiece that instructs the production line on how it should be worked. This way, the development of the value-creation chain is turned completely on its head. It leads away from the central management and rethinks the manufacturing process entirely.

In global competition, this means that wage-intensive locations can particularly benefit from the automation of production processes by means of cutting-edge production technologies and embedded systems. Smart factories create products that remain competitive on a global scale thanks to a high level of quality, individuality, efficiency and speed, and thus help to tap into new markets.

 

Small and Medium-Sized Enterprises

This development is increasingly having an effect on small and medium-sized businesses. It opens up opportunities to be present and act quickly and flexibly in a volatile environment.

Intelligent measuring and evaluation systems are an important key here. It is optical processes and components in particular that play a big role when it comes to digitalisation of production processes, since they supply comprehensive information about product quality, for example, promptly and readily.

With increasing automation, measuring technology can be incorporated even more thoroughly in the production process. Data are available not merely following laborious measurements in the measuring room, but to flow into the networked system immediately. Comprehensive measuring processes boost transparency in production, but require suitable software solutions and compatible interfaces that make reliable communication between the systems possible.

Intelligent measuring technology that can be integrated straightforwardly into the existing IT infrastructure can be an important signpost in the direction of Industry 4.0. Optical systems score points for their speed and precision. With carefully considered interfaces in what is almost a “plug-and-play” process, they can both measure as well as supply the data for further processing. Be it for an “early-fail” diagnosis or to generate a faster, more precise improvement process through continuous feedback of relevant information from the production to the product development or to tool and testing equipment construction.

Further possible applications involve prototype construction, or reverse engineering and product development. Consequently, products can be developed so that they are better suited to the production process or suppliers can be given the ability to produce with adaptations to suit the specific requirements.

Where required, intelligent systems can enable the development of quality assurance measures that are already heading step-by-step in the direction of digitalised production, even if the IT structure does not yet permit full flexibility. Investment costs can be adjusted step-by-step to relevant requirements along the entire value creation chain.

Reshaping Working Environments

Automation will change the workplace structure within the company. In fact, the question of the precise impact in relation to the labour market cannot yet be answered definitively.

Certain trends are nevertheless taking shape. Monotonous routine tasks or activities that can be risky to health or burdensome when carried out by people are increasingly being executed through automated processes or with the help of robots.

Here, collaborative robot systems offer an entirely new form of cooperation between human and machine. Intelligent assistants ensure a high level of reliability and productivity, which strengthens companies at wage-intensive locations and thus secures jobs. A further plus point is that if the employees are relieved optimally by means of automated solutions, this creates more freedom for areas of work in which their creativity and efficiency is required, be it in the development of new products, services or processes.

However, Industry 4.0 will not succeed without human labour when it comes to overseeing the automated processes. The control elements for managing the machines will thus become much more important, for example. With their user-friendly interfaces, they ensure that processes run intuitively and can be controlled safely. The latest generations of control elements can be designed to be so highly flexible that technicians as well as measuring and software experts will be able to use them with the utmost precision. Current human-machine interfaces, for example, make use of the properties of user interfaces from entertainment electronics.

If these learnt structures are integrated into areas of work, they can help employees with the application and can boost motivation and the willingness to assume responsibility. Ongoing further training measures will make a key contribution to a company’s success in the future as well. Yet with user-oriented control elements, labor and therefore costs can be reduced considerably.

Automation solutions can:

  • Take over dangerous, monotonous or strenuous tasks
  • Operate in areas not fit for humans
  • Increase productivity and secure wage-intensive locations

 

 

Industry 4.0 Building Blocks

On the path towards Industry 4.0, measuring and imaging technology companies such as Faro can deploy high-precision instruments both for tactile and for non-contact recording of objects, whether by means of visual imaging procedures, tactile measuring arms or laser scan technology.

In addition, there are various software solutions that enable both communication between all measuring systems and interfaces to all common software applications. Measured data can be recorded quickly where required in multi-sensory mode and optimally prepared for further use. This cuts complex programming tasks and costs for system integration.

These competence building blocks are used to develop individual solutions directly tailored to the requirements of its customers, from individual building blocks through to complete solutions.

Top 4 Industry 4.0 Trends In Manufacturing

Top 4 Industry 4.0 Trends In Manufacturing

There are new possibilities offered by big data, 3D printing, machine learning and augmented reality in the manufacturing industry. Leveraging on these into a new way of doing business is a key factor in Industry 4.0 to gain a competitive edge, and for companies to be more profitable and scalable. By Farah Nazurah 

The global Industrial Internet of Things (IIoT) market is expected to reach US$195 billion by 2022, growing from US$113 billion in 2015, at a compound annual growth rate of 7.89 percent between 2016 and 2022, according to a market research report by Markets and Markets. A key factor identified is the need to implement predictive maintenance techniques in industrial equipment to monitor their health and avoid unscheduled downtimes in the production cycle.

In the metrology segment, the view for Industry 4.0 in terms of part inspection is to increase quality and maximise throughput, whilst reducing costs right down the production line, making manufacturing processes faster and more accurate. Multi-sensor metrology alone is not enough to seize the maximum potential of the production line; integration of autonomous processes and hardware as well as complete connectivity is needed to fully embrace manufacturing of the future.

Four Industry 4.0 trends will be discussed in this article—from big data, predictive maintenance, augmented reality to cybersecurity. Industry players should be aware of these trends as they have already begun to affect many aspects of industrial automation going forward.

Industry 4.0 is the no longer the future of the industry, and the time is now for companies to implement intelligent manufacturing practices.

1. Big Data/Data Analytics

Big data describes the large volume of data, both structured and unstructured. Insights from big data can enable better decisions to be made—deepening customer engagement, optimising operations, preventing threats and fraud, and capitalising on new sources of revenue. The majority of data created between now and 2020 will not be produced by people, but by machines as they communicate with each other over data networks.

The insights gained from big data analytics and the IIoT to drive greater manufacturing intelligence and operations performance is considered essential by 68 percent of manufacturers, according to a recent survey by Honeywell. This highlights that manufacturers are increasingly aware of the importance in big data analytics and its potential in the industry.

Exponential Growth In Big Data

The global big data and business analytics market will grow to US$203 billion over the next few years, according to a report by International Data Corporation. The growth forecast for the global big data and business analytics market through 2020 is led by manufacturing and banking investments. The rate at which data is being generated is rapidly outpacing the ability to analyse it, according Dr Patrick Wolfe, a data scientist at the University College of London. The complex nature of the information created requires solutions capable of addressing data security, privacy and flexibility issues. Dr Wolfe added that it is key to turn these massive data streams from liability into strength.

Machine tool manufacturer Mazak has developed its own data collection and analysis system called SmartBox to connect machine tools securely and intelligently. The company uses this system at several of its own facilities worldwide. Most recently, the i-Smart Factory concept in their Singapore production facility is based on the company’s accumulated knowledge on factory management.

Tomohisa Yamazaki, president of Mazak, stated that rising personnel costs is a social problem not only in Japan but also in other countries as the labour force population declines. As such, one of the most crucial issues for the manufacturing industry is to keep increasing productivity by investing in advanced production technology.

Data Analytics To Reduce Machine Downtime

A survey of manufacturing executives in the US by Honeywell revealed 67 percent of respondents have plans to invest in data analytics. The executives viewed data analytics as a fundamental component of the IIoT, and as a solution to unplanned downtime and lost revenue.

The survey revealed companies are feeling pressure to continue working under threats of unscheduled downtime and equipment breakdowns, which was viewed as the most crucial factor in maximising revenue. Employing data analytics to ensure machines are kept running at optimum level could vastly reduce and even eliminate unplanned downtime.

2. Predictive Maintenance

Predictive maintenance foresees when equipment breakdowns might arise, and it prevents machine breakdowns by carrying out maintenance. When repairs and maintenance are planned, it could save manufacturing companies 12 percent in cost savings, whereas a loss as much as 30 percent could be incurred when unplanned repairs occur, according to research by the World Economic Forum and the consultancy Accenture.

With predictive maintenance, manufacturers can lessen maintenance and servicing costs, and boost reaction times within disruptive production processes.

The unchanging objective in metal cutting manufacturing is to further increase productivity, creating added value for the customer. Heller, a milling machines and systems manufacturer, has developed its own system to improve transparency of its current machine status, by evaluating data to allow purposeful diagnostics which yields higher productivity and reduces machine downtimes. The visualisation of specific information, including status displays of axes, spindles or other assemblies, enables users to determine wear and take preventive measures in order to avoid unscheduled downtimes.

Real-time Condition Monitoring

Machine and sensor data can be catalogued and displayed in real time using Industry 4.0 software, which provides support for condition monitoring. Data visualisation is not confined to the control station, and can be accessible on any platform everywhere—from tablets, smartphones, and bigger screens, both on the production floor and in the cloud.

When the software has determined an imminent maintenance task from the pre-set specifications, the information would be sent immediately to maintenance staff. After maintenance has been carried out, staff can note down tips to improve subsequent maintenance works.

3. Augmented Reality

Augmented reality (AR) is an enhancement of a real-time display using real images alongside computer generated information. AR is associated with Industry 4.0 practices relating to smart manufacturing, and has tremendous potential to influence manufacturing industries. With augmented reality, challenges which arise with conventional 3D measurement can be eliminated.

For example, Keyence’s XM Series handheld probe coordinate measuring machine allows for an operator to perform 3D measurements via an onscreen interactive visual guide and touch probe. Augmented-reality guidance images are created automatically, and the system overlays the measurement points along with their 3D elements.

Shared programmed work instructions and measurement results in consistent measurement regardless of the operator, environment or other circumstances.

Potential Usage Scenarios

AR has numerous uses, involving different types of operations that can be executed on the factory floor—manufacturing activities such as production, and support processes such as maintenance and training.

“Some companies are concerned or even hesitant to adopt industry 4.0 practices as they are not even at the Industry 3.0 stage. However, it is possible to jump straight from Industry 2.0 to 4.0. For example, to improve standard operating procedures among plant staff that are still using physical papers for instructions, they could instead make use of augmented reality to simplify and learn new procedures,” said Lim Yew Heng, partner and managing director, The Boston Consulting Group. Some potential usage scenarios of AR are as follows:

  • Operations: any kind of operation which requires some step by step procedure can benefit from the adoption of AR—installation, assembly and machinery tool change.
  • Maintenance and remote assistance: AR is efficient at reducing execution times, minimising human errors and sending the relevant performance analytics to maintenance staff.
  • Safety management: AR allows risk and safety of operators and equipment to be managed.
  • Design and visualisation: AR provides tools that improve design, prototyping and visualisation in the design phase.
  • Training: for companies where training is a critical process involving many field technicians, AR-guided training can be effective at training staff, especially in the beginning where there is a learning curve.
  • Quality control: AR support in quality control processes enables staff to determine if products meet manufacturing standards.

4. Cyber Security

The integrated nature of Industry 4.0-driven operations means that cyberattacks can have devastating effects, evident in the unprecedented “WannaCry” global cyberattack in May this year. Cyber security strategies should be secure and fully integrated into organisational and information technology. Picking the right cybersecurity provider is essential in ensuring data is protected.

“Some of our clients have come to us and said they do not think they will be able to put up their data on the cloud as they have very sensitive data. Within their operating database, there are certain data that are more sensitive, and there are those which contain less sensitive information,” said Mr Heng, partner and managing director, The Boston Consulting Group. “They could start out with putting less sensitive data on the cloud and understand how it works first, and understand how cybersecurity providers can help them. From there, they can move towards a more balanced approach.”

Data Sharing: Increased Access To Data

Companies should consider which data should be shared and how to protect the systems, and which data that is proprietary or have privacy risks. Companies should leverage tools such as encryption for data which are at rest or in transit, to safeguard communications should they be intercepted or if the systems are compromised.

It is important for manufacturing companies to perform risk assessments across their environment—including enterprise, DSN, industrial control systems, and connected products. Data evaluations should then be applied to update cyber risk strategies.

Protecting Data

Sensitive data are not limited to sensor and process information; it also includes a company’s intellectual property or even data related to privacy regulations.

As more IoT devices are connected to networks, the risk of potential attack increases, along with risk from compromised devices. The first step companies should take is to discover all assets, especially industrial controllers. Picking the right cybersecurity provider who understands what your company needs is essential in protecting your data against cyberattacks. Transparency is important for companies with highly sensitive data therefore, ensure that third-party cybersecurity providers inform you where the information goes.

The Right Strategy Is Important

“Companies have to ask themselves why they want to create a fully automated manufacturing factory, and what value it creates for the end users. Once the staff in the company knows why this is being done, it will change the company’s culture, and they will start focusing on value delivered to the customers,” said Scott Maguire, global engineering director, Dyson. “At the end of the day, these are big investments, and companies have to plan strategies for the long-term and be willing to change their company culture.”

Manufacturing companies should embrace the positive disruptive changes that Industry 4.0 practices can bring. A digitalisation strategy which is tailored to your company’s needs should be mapped out, and disseminated to staff so they understand it is a part of the company’s new culture.

Employing data analytics ensures machines are kept running at optimum level.

 

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Augmented Reality holds vast potential and it is the future of manufacturing.

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