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2021 Metals Analysis Outlook: Optimising Production Through Connectivity

2021 Metals Analysis Outlook: Optimising Production Through Connectivity

Despite being a year of huge disruption, the year 2020 has accelerated change for many companies. Find out more in this article by Hitachi High-Tech Analytical Science.

There’s always an opportunity with a crisis. Whilst 2020 was a year of huge disruption, with industries having to cope with sudden changes in demand, issues with supply and restrictions on the ability to operate, it did accelerate change for many companies. Especially when it comes to big Industry 4.0 trends including connectivity, big data, smart factories, and sustainability.

Thanks to new technologies being deployed throughout companies, IIoT (Industrial Internet of Things) is enabling the collection of more and more information every day, including from manufacturing equipment.

Today, many analysers collect data on the instrument themselves. Our Hitachi handheld analysers, for example, are able to store measurements remotely. More models also have connectivity enabled, which is the real game-changer for enabling remote, real-time decision making. This, we predict, will be a key theme for 2021.

What Do We Mean By Connectivity?

The vision is that analytical instruments will have either Wi-Fi, Ethernet, USB, or in the future, 4G/5G functionality, depending on the industrial environment. The next step would be for analysers to have the ability to share and integrate operational technology (OT) data. But today, most of the connectivity is around data sharing and automation.

Connectivity in the future could also mean that analysers could integrate to process control systems and communicate with other machines and resources. Ultimately, the end goal is to speed up processes, optimise performance, reduce waste, and ensure product quality.

Leveraging Technologies to Make Manufacturing Greener

Industry 4.0 has uncovered an opportunity for positive action when it comes to sustainability, by leveraging technologies to make processes more efficient and greener.

Foundries, for example, have for years championed the green movement by being the ultimate recyclers of raw materials. However, many are also looking at what green technology can do to help reduce material waste. Each process step should have the right solution in place: incoming inspection, melt shop floor, central lab and outgoing inspection. Connected analytical instruments can feed data to a central point, where quality issues can be easily spotted and subsequently rectified to reduce wastage and save cost.

The same concept can be applied further down the supply chain within fabrication, but equally at OEM level. Ensuring each process step has a focused solution that enables data collection can help reduce wastage and deliver greener manufacturing.

Big Data is Power

One reason information rules in the metals industry is through its ability to make manufacturing quality assurance and control processes simpler and faster. However, whilst the quantity of data available is colossal, the question is how manufacturers turn this into something of value – recognising patterns and predicting behaviour to make informed decisions.

Even if thousands of measurements are taken each day, data from the analyser can help manufacturers optimise production in a number of ways, including:

  • Increased product quality by identifying defects at the earliest stage in the process.
  • Machine failure predictions and diagnostics leading to well-timed preventative work, reduced downtime and less risk of sudden failures that are so damaging to business.
  • Reduced costs through the use of big data for predictive analytics, shortening the quality assurance process.

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Making Use Of Big Data

Making Use of Big Data

Data is a key to start the journey towards Industry 4.0, and robust analysis of machine data can enable efficiency-optimized production, and potentially lead to new business models. Article by Beckhoff Automation Pte Ltd.

Industry 4.0 is a buzzword that was invented back in 2011. Eight years on, the industry has very much moved on from defining the term towards actual implementation.

Industry 4.0 essentially covers a wide scope, from organizational processes down to the production machines, with each part needing to play its own role in reaching towards the end goal—creating a smart factory. However, before any intelligence can happen, one should not neglect the foundation of it all, collecting suitable and sufficient data.

Another term that we commonly encounter these days is ‘big data’. Giant IT companies such as Facebook and Google have recognized that collecting and analysing huge amounts of data in a target-oriented manner delivers valuable benefits. The same experience and technology is slowly making its way to the manufacturing or metalworking industry.

Analysing machine data brings forth some benefits to the overall manufacturing process, such as allowing the system to accurately predict potential machine failures, or monitoring and reporting machine performance, just to name a few. Ultimately, the company will be able to achieve cost savings with predictive parts change, and machine performance data can help to identify areas of improvement in the production process. In addition, targeted improvement actions can be taken.

Dealing with Legacy Systems

Let’s delve deeper into data collection on metalworking equipment. Majority of the metalworking equipment that are being used nowadays are still standalone. They are not connected in any way to a central server; parameters and machine data are mainly stored locally within the controller. Companies are facing challenges to collect data from such equipment because the machine controller can either be locked, no interface for third party system connection, or just way too old. Having said that, there are still equipment in the field that are open, and companies can tap onto the existing controller to retrieve any available data.

In order to overcome such challenges, companies may resolve to one of the following options to collect data from the equipment:

  • integrate with existing controller if it’s open;
  • add auxiliary system with additional sensors onto the machine; or,
  • retrofit the machine controller to a newer system.

While multiple options of implementation are available, it is common to have a mix of solutions and multiple brands of equipment in the plant, each running with a different controller model. This also means that integration of a variety of protocol is expected. In such a diverse environment, any system added to the equipment for data collection is recommended to run with open standards, especially the types of communication protocol supported.

The data acquisition system should also be flexible enough. The system should cater for future expansion, as such projects are most likely to be implemented in phases. Users should also be able to specify if they would like the data to be stored and analysed locally, or transmitted to the server or cloud for further storage and analysis. Companies should always keep the end goal in mind, taking into consideration that the system deployed at the equipment level should be ready to connect with the systems at the IT level, be it a manufacturing execution system (MES) or an enterprise resource planning (ERP) system, to achieve final overall integration.

Simply generating enormous amounts of data is not enough, these data volumes also have to be managed. With proper analytics tool, companies can translate raw data into meaningful information that can be used to improve their production processes, improve product quality and save maintenance cost.

For example, bearing is one of the components in the machine that requires replacement most often, and usually vibration of the machine is monitored to predict bearing failure. Hence, with sufficient amount of vibration data, companies can then better predict when the bearing is most likely to fail with the trends observed, and execute parts change only when required. Another example will be the monitoring of energy used by the equipment—having such data will help in identifying areas for potential energy savings, and to better plan the production to maximize savings.

These are just two of the many benefits that can be achieved with data collection. When exploring solutions for data collection and analysis, system integrators are starting to look at PC-based control to handle the large amount of data expected, something a conventional PLC may not be able to achieve.

In conclusion, with the variety of solution available in the market, companies should always work with open standards and flexible system for their metalworking equipment. Data is indeed a key to start the journey towards Industry 4.0, and robust analysis of machine data can enable efficiency-optimized production, and potentially lead to new business models.



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Updates On The Progress Of Thailand 4.0

Updates On The Progress Of Thailand 4.0

Industry 4.0 has transformed the way in which manufacturing is conducted and with buzzwords such as artificial intelligence (AI), analytics, cobots and cybersecurity dominating the industry. This has resulted in emerging markets such as Thailand developing innovative solutions in order to prosper. Article by Hazel Koh.

According to the Thailand Board of Investment (BOI), Thailand 4.0 is a result of the Thai government’s vision of a new economic model, aimed at pulling Thailand out of the “middle-income trap”. And through this vision, robotics and automation technology is expected to play an increasingly important role in manufacturing. This builds on Thailand’s progress in the last three decades whereby the country grew in global rankings in terms of its automotive, electronics and electrical appliance industries, which are also the main industries that drive global robotics and automation growth. Hence, as the world’s sixth-largest commercial vehicle producer, Thailand has been using robotics and automation technology at an increasing rate.

Growth In Industrial Machinery

Duangjai Asawachintachit, Secretary General of Thailand BOI, said at the end of 2017 that, “Advanced technologies are changing the business landscape, especially in the manufacturing sector.” And he further added that, “We now see many companies transitioning into Industry 4.0, making use of AI, big data management and the Internet of Things (IoT) to seamlessly work together to exponentially increase both production and productivity.”

Therefore, it can be observed that over the past few years, manufacturers in Thailand have increasingly automated manufacturing processes and adopted the use of machinery in order to remain competitive globally. In addition, 50 percent of Thai manufacturers are considering the adoption of automation systems within one to three years while medium-sized businesses will be ready in three to five years, followed by small companies in five years or more.

This has resulted in a dramatic expansion of the Thai industrial robots industry and between 2013 and 2018, Thailand’s exports of industrial robots has increased by 133 percent.

Infrastructural And Ecosystem Support

In order to facilitate the development of Thailand 4.0, Thailand has invested in numerous support networks. For example, educational institutions are playing a role in supporting research and development as well as human resource training and this can be observed in the case of the Institute of Field Robotics (FIBO) of King Mongkut’s University of Technology, Thonburi, which is currently offering undergraduate and graduate programmes in robotics and automation engineering.

To top this off, The BOI offers a consortium of tax and non-tax investment incentives for projects that meet national development objectives in automation and robotics. For example, machinery and import duty for raw materials that are meant for export production can attain up to eight years of corporate income tax exemption while for projects related to assembling robots or automation equipment and/or automation parts, investors will be exempted from corporate tax for five years. And investments relating to robotics and automation in the Eastern Economic Corridor (EEC) will also be given another 50 percent corporate income tax reduction for an additional five years.

Future Outlook And Challenges

As Thailand builds on its vision of advance manufacturing, the workforce has to be trained in order to meet the changing industry requirements. And it has been estimated by the ILO that 56 percent of Thai-based jobs are at high risk of being automated during the next two decades. Therefore,as the government continues to focus on the development of robotics, mechanics, AI and automation, Thailand has to invest on its workforce in order to remain competitive.


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Interview With Mr. Vincent Tang, Regional Vice President Of Asia In Epicor

Interview With Mr. Vincent Tang, Regional Vice President of Asia in Epicor

Asia Pacific Metalworking Equipment News is pleased to conduct an interview with Mr. Vincent Tang, Regional Vice President of Asia in Epicor on his views on Industry 4.0 megatrends in Southeast Asia.

1. In your opinion, what are the top three megatrends that are shaping Industry 4.0 in Southeast Asia?

Industry 4.0 is a hot topic in Southeast Asia, North Asia as well as regions outside of Asia such as the U.S. The term originated in Germany and is known by different names globally. For example, in China it is known as “Made In China 2025” and in the U.S it is known as smart manufacturing.

The trends shaping Industry 4.0 does not just involve ERP systems, it involves manufacturing execution systems, the extraction of data and its translation into meaningful information, big data, product lifecycle management (PLM) and the integration of robotics into processes. This means that Industry 4.0 is a long journey and companies begin their journeys at different points. For example, some companies may begin first with the implementation of an ERP system while others may not.

In Southeast Asia, Industry 4.0 is encouraged by government support through means such as grants and funding. This has allowed the region to advance in terms of the manufacturing technologies.

2. What are the key challenges that prevent manufacturers in Southeast Asia from digitalising and integrating artificial intelligence as well as data science into their manufacturing processes?

Retaining and attracting talent is the top challenge that prevents manufacturers from digitalising. In factories that are not fully automated, factors such as the increased amount of paperwork and high surrounding temperatures and harsh external environments may contribute to staff turnovers.

Additionally, the integrated implementation of automation is a challenge to some manufacturers in the region. This can occur because manufacturers may implement automation as a phase by phase process instead of as an integrated solution. For example, the accountancy department may be automated first before the inventory control department is automated.

Finally, manufacturers may find it challenging to successfully implement ERP systems. This could be because the successful implementation of ERP systems involves more than one key user, as it is a team effort. One that involves more than monetary investments and individual contributions. For mid-market companies, they possess limited ERP resources and budgets for ERP implementation and also require ERP systems to be installed in a short period of time – typically within six to nine months. These companies also tend to require flexibility.

3. How do you suggest that the above challenges be solved?

Departments can be integrated to increase the opportunities for rapid decision making and for different issues to be highlighted.

Productivity can also be increased due to the shortage of labour globally, especially in China which is also the largest manufacturer in the world. Although labour costs in China used to be lower, factors such as the one child policy has caused labour shortages and increased labour costs. While in Southeast Asia labour shortages are less severe and labour costs are cheaper, as in the case of countries such as Vietnam, Indonesia and Thailand.

Overall, the solution that is applied needs to be an integrated end to end solution. For example, processes that range from manufacturing to scheduling to finances have to be integrated. The solution that is applied has to also be multi-dimensional, multi-language based and focused on multi-localisation. This is because of the differing regulations in different countries that would require localised solutions to cater to it.

4. In 5 to 10 years time, how do you think the manufacturing industry in Southeast Asia will evolve?

The industry will continue to grow. This is because of the China-US trade war, as a lot of manufacturing companies are considering subcontracting their manufacturing operations to countries outside of China, such as Vietnam, to overcome restrictions when it comes to exporting to the U.S. This can be seen in the case of South Korean manufacturer, Samsung, which has moved its operations to Vietnam.

Thus, in Southeast Asia, manufacturing will continue to grow and this will be facilitated by Industry 4.0 and infrastructural developments such as the Belt and Road Initiative that will connect Bangkok and China via a high speed train.

5. What are your thoughts on the Industrial Transformation Asia Pacific event? Do you think this is the right time for an event like this?

The event occurred at just the right time. Different countries are at different stages of their development and the delegates that attend the event are keen to find out how they can engage in Industry 4.0 and where they are in their journeys towards Industry 4.0.

The event has also attracted over 1,800 registrations and I am able to meet a lot of individuals from Indonesia, Thailand and China. Everybody is working around the concept of industrial automation and it involves areas such as PLM, big data, manufacturing execution systems (MES), robotics, ERPs and integrated solutions.


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EuroBLECH 2018 Launches In Hannover

EuroBLECH 2018 Launches In Hannover

GERMANY: EuroBLECH 2018, the 25th International Sheet Metal Working Technology Exhibition, has opened its doors at the Hannover Exhibition Centre in Germany. Until Friday, the 26th October 2018, a total of 1,507 exhibitors from 40 countries will present the latest technologies along the entire sheet metal processing chain. With a net exhibition space of 89,875 square metres, this year’s EuroBLECH has further grown in exhibition space by 2,000 square metres, compared to the last event in 2016.

This year, 58% of exhibitors at EuroBLECH come from outside Germany. The percentage of international exhibiting companies has thus increased by a further 4% with the biggest exhibitor countries coming from Germany, Italy, China, Turkey, the Netherlands, Spain, Switzerland, Denmark, the USA and Austria.

For this year’s 25th edition of EuroBLECH, the main topics are Industry 4.0, big data and digitalisation. These new trends and developments offer advantages in terms of new business approaches, streamlining and simplifying processes as well as the improvement of productivity and efficiency. Therefore, the organisers, Mack Brooks Exhibitions, have chosen the motto ‘Step into the digital reality’ as the overall theme of EuroBLECH 2018. Visitors can expect the most comprehensive technology range in terms of industrial digitalisation of sheet metal working at the show this year.

EuroBLECH will also present the entire sheet metal working technology chain, ranging from high tech systems to conventional machinery. This covers sheet metal, semi-finished and finished products, handling, separation, forming, flexible sheet metal working, joining, welding and surface treatment, processing of hybrid structures, tools, additive manufacturing, quality control, CAD/CAM/CIM systems and R&D. The show attracts sheet metal working specialists at all management levels in small and medium-sized companies as well as in large enterprises. Visitors include design engineers, production managers, quality managers, buyers, manufacturers, technical directors and experts from associations and R&D.

EuroBLECH Awards Ceremony

The winners of the EuroBLECH Online Competition ‘Step into the digital reality’ will receive their prizes at the official awards ceremony. The ceremony will take place on Wednesday 24th October 2018, at 14.00 hrs, in Hall 16, Stand C51. Prizes will be awarded in the following three categories: Digital Transformation, Best Start-Up and E-Mobility.

More information on EuroBLECH can be found at:


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Jack Ma’s Vision Of New Manufacturing – A Silver Lining To The US-China Trade War?

Jack Ma’s Vision Of New Manufacturing – A Silver Lining To The US-China Trade War?

CHINA: Amid the economic strain that the US-China Trade War has caused, it has also resulted in unique business transformations and immense Chinese technological evolution. An example of which would be Jack Ma, co-founder and executive Chairman of Alibaba Group Holding’s vision of New Manufacturing. A novel concept that utilises the Internet Of Things (IoT), cloud computing , artificial intelligence (AI) and big data to mass create highly customised consumer products in a market that is fast leaning towards personalisation.

Additionally, through the integration of New Manufacturing and New Retail, online and offline retail experiences can be connected to and funneled towards the manufacturing pipeline to ensure that consumer feedback are quickly relayed to manufacturing operations, outputs and inventory stocking. A proposition that Ma predicts will drive the Chinese economy forward and reinforces his statement that “If we use machines and data, to integrate and digitalise, we will change the economy”.

Hence, in the face of rising tariffs from the trade war, Ma’s vision alongside the Chinese government’s “Made in China 2025” industrial master plan aims to reduce the digital gap between China and the West and ultimately, minimise China’s dependecy on imported technologies. A goal that Alibaba is striving towards through strategic partnerships, the establishment of new technology companies as well as acquisitions – as most recently seen by the company’s progress in semiconductor R&D and its production of its own CK902 series of smart chips. A “core technology” that Ma strongly believes should be made locally as China has the largest number of internet users in the world.


Real-Time Data For Process Optimisation: Practical Software For Machining

Real-Time Data For Process Optimisation: Practical Software For Machining

Industry 4.0, Big Data, Internet of Things (IoT), digitalisation, networked production – these topics seem to be everywhere. So much so that the mere mention of the buzzword “Industry 4.0” causes uncertainty among many technicians in medium-sized companies. This is because they are unsure what “Industry 4.0” will actually mean for their own day-to-day work and their future-proof production strategy and production planning. By Florian Böpple, Digital Manufacturing Manager at Walter.

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How Big Data Is Changing The World Of Manufacturing

How Big Data Is Changing The World Of Manufacturing

The manufacturing sector has played a very important role as an economic engine of countries across the world.  Global competition in this sector is fueling a race to convert factories into digital hubs.  By Dr. Darshan Desai and Om Desai, Experfy

Despite the differences in the role of the manufacturing sector in advanced nations compared to that of emerging economies, disruptive technologies, big data, and digital transformations have made their mark on companies in this sector around the world, and have opened up tremendous opportunities for these companies. This is especially relevant for the Asia-Pacific region. According to new figures released by Microsoft, if the region’s manufacturing sector embraces these opportunities and unlocks the potential of digital transformation, the GDP of the whole region can increase by US$387 billion by 2021. According to this study, companies in this sector are likely to invest more in big data analytics, cloud, and Internet of Things solutions this year. While these companies are exploring ways to leverage big data and analytics to gain a competitive advantage, it’s a good time to take a closer look at how big data and the Industrial Internet of Things (IIoTs) can have a transformative impact on the manufacturing sector.

Big Data And IIoTs

Big Data And IIoTs

Image Source: Experfy

For centuries, we have used data to inform our decisions. This has been increasingly significant, as today, explosive amounts of data are being created every minute. Every action we take leaves digital footprints. On top of that, the amount of data created by consumer and industrial machines is also growing. Smart home devices can generate data and communicate with each other, while industrial machinery is increasingly able to use sensors to gather and transmit data.  The term “Big Data” refers to the collection of all this data, structured or unstructured, human or machine generated, and our ability to use it. This concept is still evolving, and is considered the driving force between many revolutionary waves of digital transformation, like artificial intelligence and the Internet of Things.

The Internet of Things generally refers to a giant network of connected things that includes interactions and interconnections between people and things, people and people, and things and things. The IIoT or Industrial Internet of Things is a subset of the Internet of Things (IoT). Accenture estimates that the Industrial Internet of Things (IIoT) could potentially add an additional US $14.2 trillion to the global economy by 2030.

Potential Impacts And Advantages

Big data analytics and the IIoT can help manufacturers in multiple ways in many different applications. Generally speaking, these disruptive tech innovations are helping manufacturers enhance their security and automation, reduce their financial risk, eliminate production downtime, and increase the quality of processes and products. These benefits of big data are far-reaching and used in all areas of operations, from product quality and stock control, to supply chain optimisation and improved health and safety. The potential impacts and advantages of big data analytics and IIoT in the manufacturing sector can be categorised into four broad categories: predictive maintenance and automation, productivity and efficiency gains, supply chain management, and quality management.

Predictive Maintenance And Automation

With increasing IT investment in the manufacturing sector, a range of off-the shelf software for tapping and integrating data sources, analysing big data, and for closing the loop in optimising processes including manufacturing is now becoming available in the market. The driving force for automation and IT integration is companies’ overall goal to gain actionable data-driven insights to improve products and processes, which can be enabled by IIoT and big data analytics.  For example, manufacturers use inexpensive sensors to reduce condition-based monitoring and maintenance in machines. Wireless devices, along with big data processing tools, make it affordable and easier to mine actual performance data and gain actionable insights to maintain equipment health. A recent article published in The Stack magazine provides an excellent example of the tech giant Intel using big data analytics for predictive maintenance, more specifically, for predicting equipment failure in one of their microchips. They were able to gain a 50% reduction in maintenance time, 25% higher yields, and a 20% reduction in the cost of spare parts, which all added up to $3 million saved. Big data is an opportunity for manufacturers to improve process performance, reduce waste, focus on better products, and produce products more efficiently.

Productivity And Efficiency Gains

Productivity And Efficiency Gains

Image Source: Experfy

Data-driven manufacturing is driving efficient and responsive production systems. Manufacturers have been able to boost their productivity by understanding plant performance and measuring the operating data of individual machines, which was made possible by analyzing large data sets. Effective and efficient sales and operations planning processes are very crucial to the productivity of any manufacturing company. These processes can create a factory’s load forecast over a period of time, which can help a company decide which products it needs to manufacture at which plant.  These types of plant loading decisions can affect the operational and financial performance of a company. Big data analytics and data points like historical load, industrial record, completed projects, and customer patterns can help optimise plant loading.

Supply Chain Management

Big data analytics and IIoT can provide manufacturers with increased access to real-time supply chain information. When plants are connected to suppliers, all parties in the supply chain can access information and monitor material flow, interdependencies, and product manufacturing cycle times. This type of real- time monitoring of supply chain information can help quickly discover issues, reduce inventory, and as a result minimise capital requirements.

Quality Management

A significant amount of a manufacturer’s annual revenues can be lost through defects in the production process. Many quality issues can be spotted and rectified as soon as they arise by analyzing real-time data from sensors on the production line. Big data use in manufacturing and quality management can reduce product, assembly, and quality management costs for manufacturers. With such large success in cutting cost, many companies are interested in leveraging big data and predictive analytics to increase return on investment.

Concerns And Challenges

A Harvard Business Review article points out a few concerns and potential challenges the companies in the manufacturing sector may face in reaping the fruits of big data analytics IIoTs. According to the article, in addition to the culture and paradigm shift from time-triggered control systems to event triggered control systems, significant challenges can be related to the integration of legacy systems, and creation of unified data. A significant problem is legacy manufacturing equipment that consists of systems that haven’t been upgraded in parallel with the technological innovations.  For many organisations, total replacement of expensive legacy systems isn’t always an option. The challenge, then, is to think of innovative ways to integrate existing systems with tools that allow them to communicate with the newer, more streamlined systems that make up the IIoT. The good news in this situation is that it’s possible to leverage the benefits of big data and IIoT without ripping and replacing existing systems.

Despite the benefits and significant potential impact of big data and IIoT, to get beyond the hype, managers need to understand the underlying challenges. In these types of situations, taking an incremental approach can help companies unlock the transformative value of big data and IIoT.

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