A hybrid performance prediction method for centrifugal compressors based on single-zone and two-zone models

A hybrid performance prediction method for centrifugal compressors based on single-zone and two-zone models

Abstract

High-accuracy models are essential for rapid performance estimations and reliable parameter refinements during the preliminary design of centrifugal compressors. In this paper, a hybrid performance prediction method is proposed by combining the loss models of the single-zone method and the division idea of the two-zone method. Physically-based loss models are adopted for the jet zone analysis in substitute of the empirical parameters in the two-zone method. Two additional parameters are introduced for the wake zone analysis to implicitly evaluate the loss not fully understood in the single-zone method. For these two-zone parameters, prediction models are proposed by first analyzing the dominant factors from one-dimensional level and then extracting the coefficients from diverse datasets with statistical techniques. The hybrid method is validated on four centrifugal compressors with flow coefficients ranging from 0.09 to 0.58 and pressure ratios up to 8.5. The results show that, compared with the single-zone and two-zone methods, the hybrid method provides more reliable performance predictions with higher accuracy in the whole operating range.

Centrifugal compressors are widely applied in aircraft engines and their efficiency is of paramount importance. This is why developing a high-accuracy one-dimensional performance prediction method is highly desired. Precise performance prediction or analysis enables designers to make quick assessments and necessary refinements of the geometry during the early design stages of centrifugal compressors.

The current one-dimensional performance prediction methods are divided into three categories: zero-zone, single-zone, and two-zone. The zero-zone technique is a non-dimensional map analysis method for which efficiency is predicted from empirical correlations according to non-dimensional parameters such as tip-speed, Mach Number and flow coefficient. These techniques are used in the early design stage, and for the limited inputs requirements, they only give fairly rough estimations.

The single-zone technique, which is more-geometry-based, divides the loss in the centrifugal compressors into numerous individual components and a loss model formulated for each component. Researchers have proposed several collections of loss models, but purely empirical and semi-empirical models in these collections significantly limit their application.

The two-zone technique, which is a more advanced method, has been proposed to model jet-wake flow pattern in flow analyses. However, effectiveness parameters may vary significantly with flow parameters such as Rynolds number, blockage, blade-loading, incidence, Mach number, etc. Even when the effectiveness parameters are set as constants, the lack of a detailed guideline for parameter selection forces designers to rely on their own experience. The fact that there is still no specific definition of the two zones to differentiate between the primary and secondary zone is another shortfall of the two-zone method.

In all, the two-zone method falls short of a basic guideline for parameter selection despite its upside of trying to model real flow structure with introduced parameters. The single zone method predicts the loss from basic physics, but some loss mechanisms aren’t sufficiently understood yet. This is why PhD candidates Pengcheng Xu, Liming Xuan and led by Professor Zhengping Zou from Beihang University in China developed a new hybrid performance prediction method combining the loss models of the single-zone technique and the division idea of the two-zone technique. The researchers introduced two additional parameters for wake zone analysis to specifically analyze the loss mechanisms not clearly understood in the single-zone method. Their research work is currently published in journal, Aerospace Science and Technology.

Going by the two-zone definition, the proposed hybrid system splits the flow into a jet zone and a wake zone. The authors adopted the well-understood models in the jet zone analysis as an alternative to the empirical parameters of the two-zone method. In the wake zone analysis, the researchers introduced two parameters as an alternative to the endwall loss model in the single-zone model. For the first time, the authors were able to completely define the wake zone and proposed a sensitivity analysis. They then presented the loss models for the jet zone and parameter selection guideline for the wake zone. The authors finally validated their proposed hybrid method on four centrifugal compressors and compared the results with the single and two-zone methods.

The novel hybrid method implicitly took into account the endwall loss with the two introduced wake zone parameters on the assumption that all the endwall loss was contained in the wake zone. Models for the wake zone parameter predictions were proposed by evaluating the dominant factors from one-dimensional level. The authors then extracted the coefficients from sufficient datasets using statistical methods. They found it to be convenient to update them from corresponding database when a new design feature needs to be introduced. The researchers then validated the hybrid method on four centrifugal compressors, and they were able to accurately predict both the shape and performance curves values. They reported an efficiency error of less than 1% at design points and no more than 4% at off-design points.

The findings of Pengcheng Xu and colleagues show that compared with the single-zone and two-zone methods, the proposed hybrid method gives more reliable and accurate predictions in the whole operating range.

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About the author

Zhengping Zou is a tenured full professor as well as a doctoral supervisor in Research Institute of Aero-Engine and National Key Laboratory of Science and Technology on Aero-Engine Aero-thermodynamics, School of Energy & Power Engineering, Beihang University, Beijing, China.

Pengcheng Xu is a Ph.D. candidate supervised by Prof. Zhengping Zou in National Key Laboratory of Science and Technology on Aero-Engine Aero-thermodynamics, School of Energy & Power Engineering, Beihang University, Beijing, China.

Liming Xuan is a PhD student of Beihang University, following Prof. Zhengping Zou, Beijing, China. He obtained bechelor degree in thermal energy & power engineering from Harbin Institute of Technology in 2014, and master degree in power engineering from University of Shanghai for Science and Technology in 2017.

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؟How to Choose an Industrial Face Mask

How to Choose an Industrial Face Mask?

by Camille Rustici

The COVID crisis has highlighted the need for protective masks to fight the virus. But long before surgical masks and N95 respirators became part of our daily lives, face masks were already in daily use in the industry.

With the coronavirus pandemic and the obligation to wear filtering facepieces decreed in many countries, two families of masks have been popularized: surgical masks and FFP respirators /N95 masks.

If a surgical mask is a disposable medical device only used in the medical field, the respirators used in industry are personal protective equipment (PPE) and offer respiratory protection.

What are the different types of respirators? How do they offer protection? Which respirator for which applications? How to wear a facepiece? Our article will give you some piece of advice to help you choose the most suitable equipment for your industrial needs. We will only focus on PPE. If you want to know more about medical masks, read this article.

In the industry, filtering facepieces are mandatory for anyone working in a dusty environment with exposure to hazards (fumes, gases or other toxic substances). They protect the wearer from all particles and projections that could be inhaled and prevent him/her from harmful consequences for his health.

Insulating and Filtering Masks

Different types of industrial equipment exist, insulating masks and filtering masks. Choosing one instead of the other implies taking into consideration the type of contaminant the wearer is exposed to and the oxygen level in the work environment.

Both filtering and insulating masks offer protection against dust, gas, fumes, vapors and aerosols. While the filtering ones are equipped with filters that retain contaminants and purify the air breathed by the user, insulating masks are supplied with air that originates from an uncontaminated source. Therefore, they offer superior protection to all other masks because the user is permanently isolated from the contaminated area.

Insulating masks are essential for long-term work in confined environments (for example in sewers), with low oxygen levels (below 17% ), or when the concentration of the contaminant is too high and the contaminant cannot be filtered.

Those full face masks protect the eyes, the nose and the mouth and can be self-contained or non-self-contained.

- With a self-contained device, the user carries an oxygen cylinder connected to the mask via a hose. The user is therefore free to move around the work area. The device does not involve a filter so the user is constrained by the duration of the cylinder’s autonomy.

- With a non-autonomous device, the user has a supply of clean air via a hose connected to a compressor located outside the polluted work area. He is therefore permanently connected to this hose and must therefore be more careful with his movements.

Filtering masks can only be used in oxygen-rich environments (with oxygen levels above 17%) and are suitable for short-term work.

- The most famous ones are the FFP1, FFP2/N95 and FFP3 respirators.

- These single-use filtering facepieces protect against contaminants such as dust, particles or viruses with a maximum use time of 8 hours.

Wearing a respirator can be very uncomfortable (heat inside the mask, breathing resistance). Some masks are equipped with an exhalation valve that improves the user’s comfort. This valve allows air to pass through when breathing out and closes when breathing in. Particles do not penetrate the mask, but the exhaled air is not filtered and can therefore contaminate the outside environment.

The Mask Efficiency Classes

Full and Half Masks

Depending on the type of pollutants and their concentration in the work environment, the wearer can choose either a half a full mask.

Half masks are filtering equipment that protects the respiratory tract (nose, mouth and chin) without compromising the field of vision. They are effective against dust and particles and are sufficient in environments that are not hazardous to the eyes.

- Soft silicone half-masks are reusable, offer comfort to the user and can be worn for long periods.

- Lighter, disposable half-masks contain neither latex nor silicone but allow the user, thanks to their low nasal position, to wear safety glasses for example.

Full face masks protect the nose, mouth and chin and in addition cover the eye area. They are recommended when there is a risk for the eyes as they guarantee a good seal and maximum protection for the operator.

They are effective against toxic gases, fumes and vapors in oxygen-rich (full-face filtering masks) and oxygen-poor (full-face insulating masks) work environments.

- Single-filter full-face masks are made of elastomer or silicone. Some models are equipped with a panoramic screen for a better field of vision.

- Double-filter full-face masks are equipped with a double air filter system with a valve that allows air to escape better. This provides greater comfort for the user and also prevents fogging.

 Full face masks are widely used in the chemical, pharmaceutical, automotive and gas industries.

Whether you choose a full-face mask or a half-face mask, you will have to choose the right filters. There are 3 types of filters: gas filters, particulate filters and combination filters.

1- Gas filters protect against toxic vapors, gases and chemicals.

2- Particle filters protect against dust, smoke, steam, microorganisms and viruses.

3- Combination filters combine the characteristics of gas and particle filters and are required, for                example, to protect against aerosols and vapors.

What are the Standards?

Respirators are tested in the direction of inspiration (from outside to inside). The tests take into account the efficiency of the filter and leakage to the face.

In Europe, they must meet the European standard EN 149: 2001 which has three classes of disposable particulate respirators (FFP1, FFP2 and FFP3).

1-FFP1 refers to the least filtering of the three masks with an aerosol filtration of at least 80% and leakage to the inside of maximum 22%. This mask is mainly used as a dust mask (home renovations and various types of work).

2- FFP2 masks have a minimum of 94% filtration percentage and maximum 8% leakage to the inside. They are mainly used in construction, agriculture, and by healthcare professionals against influenza viruses.

3-  FFP3 masks are the most filtering mask of the FFPs. With a minimum filtration percentage of 99% and maximum 2% leakage to the inside, they protect against very fine particles such as asbestos.

In the United States, respirators must meet NIOSH (National Institute for Occupational Safety and Health) standards. Within this standard, there are several classes of respirators depending on the degree of oil resistance:

1- Class N: no oil resistance. A distinction is made between N95, N99 and N100. The number after the letter indicates the percentage of filtration of suspended particles.

2- Class R: mask resistant to oil for up to eight hours. Here again, a distinction is made between R95, R99 and R100.

3- Class P: a completely oil-resistant mask.

How to Wear a Face Mask? The Importance of Fit Testing 

Filters are essential to ensure a respirator offers the right protection and filtration efficiency. But that is not all. A face mask must also be worn correctly to guarantee full protection and minimum leakage. When badly worn, even the best respirator becomes meaningless.

Fit testers are here to make sure that respirators fit well on a person. American company TSI manufactures quality instruments among which is the PortaCount Respirator Fit Tester 8040. Last year, we spoke with Oliver F. Bischof, Director of Sales – EMEA at TSI: 

Many countries follow standards that demand that everybody who wears a respirator for work has to be fit tested. In the United States and in the United Kingdom, every operator who needs to wear a respirator for work has to be fit tested. In France and in the Netherlands, only the people working in the asbestos removal and cleanup industries have to be fit tested.

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Hand in Glove: BeBop Sensors

Hand in Glove: BeBop Sensors 

With the launch of Forte Data Gloves from BeBop Sensors an immersive experience in virtual or augmented reality is now at the fingertips of a spectrum of industries.


The award-winning technology offers a hands-on experience and sensation of “touch” within a VR environment, explains Keith McMillen, company CEO.
Described as “affordable, high performance and ultra-comfortable,” the wireless data glove, which uses smart fabric sensor technology, is suitable for a wide range of applications.
These include wearable, industrial and human uses, as well as possible applications in sports; the automotive and medical industries; the military; outdoor wear; virtual reality; gaming; and musical instruments.

 They were originally designed to remove the ‘virtual’ in VR applications. Existing devices already had a great display providing a visual experience akin to reality and the audio was superb, but there was no touch feeling. In a VR environment, you could see your virtual hands, but the computer never knew where they were in real-time, it approximated.

SUPER SENSITIVE

Mr. McMillen, a musician,inventor and owner of Keith McMillen Instruments (KMI) – says early versions of VR gloves were “clunky.”

They were tethered to the computer, so your hand felt the constant tug of a cable, undoing the intended experience, whereas BeBop Sensors Forte Gloves are wireless. They work for eight hours on a single charge via USB and can communicate via Bluetooth; one size fits all; they’re light and the sensors are super sensitive and accurate.

The glove features 10 smart fabric bend sensors located above each knuckle with bend accuracy and repeatability +/- 1.5 degree and high sensor speeds of 500Hz.
A nine degree inertial measurement unit (IMU) provides extremely low drift and reliable pre-blended accelerometer and gyro sensor data.
In gaming, the gloves offer a trigger speed which matches the visuals, with no lag.
With the haptic actuators in the gloves, players can not only see precisely where their hand is, but also each of their fingers. 

 VARIED APPLICATIONSCustomers in the industrial and automotive sectors who were using other BeBop sensors created applications on their own with the gloves, Mr McMillen explains:

 In an industrial setting, a worker wearing our gloves can bring a lot of data back to the workplace designer. They can prevent injuries; they can design work so that the pressure applied to someone’s hands is within what is acceptable by medical standards. There are a whole host of applications associated with this.

The data is gathered by the gloves and passed on to the customer who manages it.
Each of our customers in the industrial, medical and automotive industries has different ways of managing the data. The formats, the analysis and resulting output are specific to their application needs.
The affordability comes down to the manufacturing process. The fabric is made in rolls and coated with the company’s proprietary nanomaterials that give the sensors the properties.
Other smart fabric products from the company include the BopPad drum pad. 

We have also built smart fabric sensors into car seats, steering wheels, foot pressure diagnostic equipment, hospital wheelchairs, patient beds, sports helmets and shoulder pads. We have an endless list of applications for our products. 

ABOUT THE AUTHOR

Abigail Saltmarsh

Abigail Saltmarsh is a freelance journalist with 25 years’ experience for industry publications (Packaging Europe) and national magazines (The New York Times, International Herald Tribune). 

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Residual stress modelling in laser welding marine steel EH36 considering a thermodynamics-based solid phase transformation

Residual stress modelling in laser welding marine steel EH36 considering a thermodynamics-based solid phase transformation

Low alloy steels are one of the most used materials in structural applications owing to their excellent properties such as ease of manufacturing, good toughness, and high strength. Among the available material joining methods, welding is undoubtfully the most suitable. This has led to significant research amongst scientists over the past years with the aim of improving the manufacturing processes. Generally, there are different types of welding whose application depends on the types of material and the intended application. Consequently, the microstructures and mechanical properties of these welds affect the properties and functionality of the materials and their entire structures in general.
Recent studies have shown significant improvements in the investigation of the joint performance of high strength steels using the residual stress, microstructure and weld pool flow. Unfortunately, considering the different nature of the arc welding and marine welding, the aforementioned criteria are insufficient to assure high-quality welding in marine manufacturing.
To this note, Huazhong University of Science and Technology scientists: Dr. Youmin Rong, Ting Lei, Dr. Jiajun Xu, Professor Yu Huang, Professor Chunming Wang assessed the distribution of residual stresses in laser welding in marine high strength steel EH36. In particular, a finite element model was designed by taking into consideration the solid transformation based on thermodynamics. Their research work is currently published in the journal, International Journal of Mechanical Sciences.
Briefly, the research team assessed the phase transformation and its effects of the residual stress by further taking into account the response of the microstructure to strain in laser welding marine high strength steel. Next, the distribution of the temperature was investigated using a heat source model while on the other hand, thermodynamics of the solid phase transformation was used in determining the microstructure fractions. To actualize their study, the research team experimentally verified the prediction accuracy of the designed model based on the residual stress, microstructure and weld profile.
The authors uncovered the usefulness of the index increment double cone method in fitting the penetration resulting from laser welding. As such, they recorded prediction errors of 11.06%, 10.24% and 6.69% in UW, MW, and BW respectively. On the other hand, a prediction error of 10.372% and 5.6435 were observed in the microstructures of the laser-welded EH36 and in particularly for martensite and ferrites. This was attributed to the influence of the weld microstructures on the strain and residual stresses of the material. However, it was worth noting that the heat affected zone, and not the center of the fusion zone, produced the maximum stress.
Therefore, the Huazhong University scientists successfully proposed a finite element model for not only accurately predicting the residual stresses in laser welded EH36 steels but also providing a basis for minimizing the welding associated stresses. Furthermore, considering the stability if the plastic strain without the need for external forces, the study will advance marine manufacturing through high-quality welds.

About the author
Dr. Youmin Rong, Assistant researcher/Postdoctor, State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, China.
Prof. Yu Huang, State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, China.

Ting Lei is a doctor of Mechanical and electrical engineering. He received his MS and BS in Mechanical Engineering from Huazhong University of Science & Technology and Changchun Institute of Technology in 2006 and 2010,

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Are Fully Self-Driving Vehicles a Distant Dream?

Are Fully Self-Driving Vehicles a Distant Dream?

Today self-driving cars are rapidly clocking up road kilometres across the world. Yet a growing sense of the remaining hurdles that need to be overcome by driverless tech developers – coupled with a series of fatal accidents involving self-driving cars – has eroded confidence and exposed the bold claims of some companies as ungrounded hype.

Autonomous car technology is already being developed by the likes of Nissan, Byton, Mercedes and, of course, Tesla. More than 50% of US cities are currently preparing their streets for self-driving vehicles. The burgeoning number of experimental driverless cars on our roads has, unsurprisingly, given the impression that the arrival of safe and reliable fully autonomous vehicles is just around the corner.

Complex Challenges

Self-driving vehicles already have a far better safety record than their human-driven counterparts. Their performance is largely the product of machine learning algorithms that have been fed terabytes of data about street architecture, the laws of the road and dynamic driving conditions. Yet the biggest challenges – anticipating human behaviour and dealing with nuanced driving scenarios – still present major obstacles, says Paul Newman, professor of robotics at the University of Oxford and founder of Oxbotica, a UK-based company that builds driverless cars.

What’s hard is all the problems with driving that have nothing to do with driving. Many potential scenarios that a driverless vehicle could find itself having to handle simply aren’t covered by the laws of the road.

Jack Stilgoe is a sociologist at the University College London and studies the social impact of technology. For him,

People are mischievous. They don’t behave rationally or logically, which makes predictive modelling hugely difficult.

Degrees of Autonomy

The self-driving vehicle sphere is dominated by six so-called levels of autonomy. These range from none at all at Level 0, through to complete autonomy (equal to that of a human driver) at Level 5. Most automakers are currently focusing their efforts on Level 4, where genuine autonomous driving systems kick in. A Level 4 vehicle is capable of completing an entire journey without driver intervention, but will probably still feature a steering wheel and pedals for situations where the human passenger may have to take control.
Both Ford and Volvo have recently stated they will offer Level 4 cars by 2021.

Volvo is making use of the DRIVE platform from American tech company NVIDIA, which the latter is marketing as the world’s first artificial intelligence (AI) platform spanning the entire range of autonomous driving. NVIDIA has claimed that its software is capable of tracking a driver’s head and eye movements, and is even smart enough to read a driver’s lips. Danny Shapiro, NVIDIA’s Senior Director of Automotive explains:
NVIDIA is working on end-to-end autonomous driving solutions from Level 2+ through to Level 5 robotaxis. Because NVIDIA DRIVE is an open, scalable platform, we can address the entire spectrum of automated and autonomous driving. 

The AI Imperative

So how far away are we from a Level 5 vehicle? According to various experts, it could be anywhere from a long time to never. John Krafcik, CEO of driverless vehicle firm Waymo, believes it will take decades for cars with advanced levels of self-driving capability to become common on roads, and that self-driving cars will always require some form of “user interaction”.
Kafcik’s argument is backed up by AI supremo Luc Julia, co-creator of Apple’s virtual assistant Siri. Julia claims fully autonomous cars will never exist because the cognitive burden of management is far too important to be entrusted to a machine.

If the eventual existence of fully autonomous cars is up for debate, there is a growing consensus among AI experts that it may be years, if not decades, before self-driving systems can be completely relied on to avoid accidents. For Oxbotica’s Newman,
I don’t believe there’s any level of intelligence that we won’t be able to get a machine to do. The only question is when 

Daniel Allen

Daniel Allen is a writer and a photographer. His work has featured in numerous publications, including CNN, BBC, The National Geographic Traveller.

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Calibration of blade tip-timing sensor for shrouded blades

Power generation has been of great significance in the production of electric energy for numerous household and industrial use. However, the rapid increase in the demand for electric power has compelled researchers to improve the already existing power generations techniques as well as develop alternative sources to supplement the deficiency. Consequently, the increasing global call for sustainable development as a way of reducing pollution through limiting dependency on fossils fuels have also contributed greatly to such developments. For instance, steam turbines which are highly used in today’s power generation stations have undergone numerous improvements to enhance their efficiency. Unfortunately, it is difficult to realize the smooth operation of turbines, especially for large power generation.
Generally, turbines are made of blades which are susceptible to numerous faults due to the natural frequency, misalignment, unbalancing and vibration. Asynchronous vibrations, for example, are more prevalent, especially for high loaded blades. On the other hand, steam turbine blades commonly undergo synchronous excitation while aerodynamic excitation is caused by resonances with nonsynchronous excitation. To this end, several methods have been devised to prevent unpredictable excitation, dynamic stresses and to improve the lifetime of blades. Blade vibrations have been measured in power stations during wide range operation because mechanical stress damages the blades thus reducing their lifetime. Unfortunately, it is expensive and difficult to use these methods to monitoring more blades due to the short sensor life, especially in corrosive environments. Therefore, researchers have been looking for alternative methods and have identified blade tip timing as a promising solution.
Recently, Zdenek Kubín at the University of West Bohemia in Pilsen in collaboration with Dr. T. Mísek, J. Hlous, T. Dadaková and Dr. J. Kellner at Doosan Škoda Power and Dr. T. Bachorec at SVS FEM investigated the use of eddy current and optical sensors in blade tip timing measurements and calibration in steam power stations. They performed measurements in various conditions and presented the detailed calibration procedure. Eventually, the obtained results were compared to the theoretical ones to validate the feasibility of the model. They purposed to improve the operation efficiency of the steam turbines, reduce damages and improve their lifespan for large power output generation. Their work is published in the journal, Mechanical Systems and Signal Processing.
From the modeled magnetic interference between the blade shroud and sensor, the authors observed that it was capable of predicting the voltage amplitude and shape of signals emanating from the sensors. Consequently, it efficiently identified the axial position responsible for bad signals production. The measurement results correlated well with the existing theoretical results. This included the calibration curve and tip deflection. For instance, best axial positions for the sensors were selected based on the calculated vibration limits and safety factors which were determined based on the measurements and calibration uncertainty. Furthermore, possible causes of such uncertainties included gage position, axial shifts, blade untwists among others.
The authors successfully developed a detailed calibration procedure for blade tip timing sensor that will help advance the efficiency and operation of steam turbines in power generation. It emphasizes on choosing the sensor size and position which was successfully validated by the developed model. The study also provides a groundwork for future studies which will promote power generation to meet the increasing demand for power.

About the author
Zdenek studied Cybernetics and Artificial Intelligence at University of West Bohemia.

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Advancing Automation Revolutionizes the Industrial Workplace

Advancing Automation Revolutionizes the Industrial Workplace

Just a few years ago, industrial robots were the stuff of science fiction. Today, as robotic systems become smarter, cheaper and more flexible – driven by trends in simplification, collaboration and digitalization – they are becoming indispensable across a wide range of industrial sectors.

Andra Keay is Managing Director of Silicon Valley Robotics. He reckons that,

Demand for industrial robotics is currently increasing faster than anyone predicted, as more countries adopt robots for manufacturing, electronics and e-commerce logistics.

Compelling Collaboration

The rise of Industry 4.0 and the development of robotics technology is redefining the relationship between automated machinery and humans in the workplace. Thanks to advanced sensors and security systems, collaborative robots (cobots) are increasingly taking up new positions next to their human colleagues, says Mark Gray, UK area sales manager for leading Danish cobot maker Universal Robots.

Collaborative automation allows businesses to find the perfect balance between the efficiency of a robot and the creativity that a human can bring to the automation process

Despite the recent demise of cobot manufacturer Rethink Robotics, cobots remain the fastest growing sector in industrial automation. A recent report from venture capital firm Loup Ventures projects cobot sales to soar from 8,950 units in 2016 to 434,404 by 2025 (by which time they will account for a third of all industrial robot sales), representing a CAGR of over 60%.

Programming cobots is typically less complex than conventional industrial robots, which lowers overall cost and improves flexibility. With an average price tag of between $25,000 and $45,000, the rise of cobots has made automation accessible to industrial SMEs. The ability to partner cobots and people boosts productivity, since it allows companies to rebalance production lines as demand varies.

In 2018, Danish cobot maker Universal Robots became the first manufacturer to sell 25,000 cobots. In June the company released its new flagship e-Series collaborative robots, which boasts a wide range of end-effectors, 17 safety features and customizable stopping time and distance.

The change to high-mix, low-volume production means people need to increasingly interact with robots in more sporadic, intermittent ways. Swiss robot robot maker ABB has recently released a product called SafeMove2, which turns industrial robots into collaborative ones by controlling the robot’s speed, force and position when a person comes near.

Upwardly Mobile

Industrial robots are rapidly evolving from physically powerful, stationary machines into lighter and more advanced mobile platforms offering a far wider range of automated solutions. These can be divided into automated guided vehicles (AGVs), and autonomous mobile robots (AMRs).

With minimal on-board intelligence, AGVs can only obey simple programming instructions, using wires, magnetic strips or sensors to follow fixed routes. In contrast, AMRs have far greater autonomy and represent some of the latest and most innovative automated devices on the market, explains Jakob Bebe of MiR, a Danish manufacturer of collaborative mobile robots.

AMRs are collaborative and designed to drive safely among human workers. They often carry high payloads in highly dynamic environments and therefore have to be very sophisticated.

Using data from cameras, built-in sensors and laser scanners, as well as complex software, an AMR can detect its surroundings and choose the most efficient route to its target. If forklifts, pallets, people or other obstacles block its path, it will safely manoeuvre around them, using the best alternative route.

While companies have been automating their production for years in order to stay competitive, there are significant gains to be made by automating materials handling. Going forwards, AMRs are likely to play an increasingly important part in lean operations across a wide range of industrial settings.

Founded in 2015, MiR is currently developing three different autonomous mobile robots; the MiR100, MiR200 and MiR500, with payloads of 100, 200 and 500 kg respectively. With switchable top modules, they can be used in industries ranging from automotive and electronics through to pharmaceuticals and logistics.

The Human Angle

Industrial robots allow companies to improve productivity, boost product quality, reduce manufacturing costs and speed time to market, says Per Vegard Nerseth, Managing Director of ABB Robotics.

Thanks to robots, people no longer have to do dull, dirty, dangerous or delicate jobs, and they no longer need to be exposed to the risks of repetitive tasks or poor ergonomics.

While robots are becoming steadily smarter, with a growing number capable of understanding environmental changes and improving performance through artificial intelligence, we are still many years away from seeing a truly cognitive industrial robot that can replace a human, thinks Jeff Burnstein, President of the Association for Advancing Automation.

Over the past 20 years, whenever robot sales in the United States have gone up, unemployment has gone down, and vice versa. The real threat to jobs is when companies can no longer compete. Robots help companies become more competitive and win new business

ABOUT THE AUTHOR

Daniel Allen

Daniel Allen is a writer and a photographer. His work has featured in numerous publications, including CNN, BBC, The National Geographic Traveller.

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What is the Future for Predictive Maintenance?

What is the Future for Predictive Maintenance?
ABOUT THE AUTHOR
Lindsay Clark






Machines that tell operators when they are going to break down, and how, are no longer a fantasy. Research from IoT Analytics, a market insights firm, says predictive maintenance is already one of the leading use cases for the industrial internet of things (IIoT). It found the market for these applications is set to grow from $2.2 billion in 2017 to $10.9 billion by 2022, an annual growth rate of 39%.
But predictive maintenance is no longer the Next Big Thing. In 2016, Dan Miklovic, research fellow with LNS Research, put forward the idea of prescriptive maintenance: analytical systems that not only predict when maintenance becomes necessary, but also prescribe actions to avoid the worst outcomes – both in terms of a technical fix and also operational changes to minimize the impact of maintenance and downtime. On his blog, he says: The idea is that the analytical tool not only can predict what is likely to occur, but it can offer ‘what-if’ analysis of alternatives to provide a scenario that can alter the outcome,”Vendors have been paying attention. IBM has already set up its Prescriptive Maintenance on Cloud platform and is set to launch a range of new related technologies using its IBM Watson set of AI services to build up its prescriptive maintenance portfolio.



Stephan Biller, vice president of IBM Watson Internet of Things, says:



Whereas predictive maintenance helps forecast where problems might occur, prescriptive maintenance might look at an entire factory of a thousand machines, with a limited workforce, and decide who can do maintenance, which machines to work on first, which batches, or items, are most important in the production run.

As well as informing operational decisions, Biller says prescriptive maintenance helps engineers. This is where IBM’s Watson services for absorbing domain knowledge and answering natural language questions will come into their own. To help with the diagnosis of a problem, Watson can “read” thousands of pages of machine instructions, documentation and maintenance history, including notes from engineers who have worked on the machine before. It can build up a picture of current based on IoT sensor data and historical performance and it will learn over time, as Biller points out:.
It can answer questions in natural language. This is really important to manufacturing. It can make your average technician perform as your best technician and make all your technicians more productive. Also, a lot of manufacturers worry that when their best maintenance engineer retires, their knowledge will go with them. The system helps to retain that knowledge.
But prescriptive maintenance goes much further than simply fixing or preventing machinery failure. Biller says it can influence company-wide operational decisions.
For example, commercial aircraft maintenance is incredibly complex. If an airline becomes aware of a non-urgent aircraft maintenance issue well in advance, it might look into how to change its flight plans in order to minimize downtime. With a wealth of analysis of historical performance data available, it could decide which routes – short or long haul – might avoid exacerbating the issue and make the maintenance job easier, Biller notes.
In a factory you might decide to make product A and not product B for a short period in the run-up to the maintenance period. You could also reassign people, taking them from operations to maintenance. All this can be optimized to get the most from a factory.
To benefit from the concept of prescriptive maintenance, industrial companies need to be aware of some difficult questions. Equipment manufacturers may themselves embed IoT sensors into their product and recommend their data solution or platform to analyze it. Their customers should be wary of such an approach, Biller says.

We mostly work with the users of those machines. Although we’re not at all opposed to working with the machine manufacturers, the vast majority of users have equipment from many manufacturers and only want one maintenance system.
While industrial firms are beginning to understand the concept of prescriptive maintenance, they need to have the right culture, approach to data and data infrastructure to benefit from it, Biller says. Most companies start with conditions-based maintenance, and move up the ladder over time, he notes.



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Machine Tools Embrace Industry 4.0 as Manufacturing Evolves Adam Turner

Machine Tools Embrace Industry 4.0 as Manufacturing Evolves

ABOUT THE AUTHOR

Adam Turner

The physical and digital worlds are colliding on the factory floor as traditional machine tooling undergoes a smart overhaul in order to meet modern manufacturing demands. We spoke with Gérard Gousset, Marketing Manager for machining systems with Italian industrial automation company Comau.

The basic concepts of machine tooling come from the earliest days of the industrial revolution, each designed to handle a different task in the mass production process. As we enter the disruptive age of Industry 4.0, these tasks are being combined into new universal, hybrid devices with the goal of shortening the process chain, says Gérard Gousset.
Ten years ago, a five-axis machining center was a very particular machine with very specific uses, Gousset says, but today there is a growing demand for such machines even for very traditional processes.

 Then there are hybrid machine tools such as combining turning and milling, or milling and additive manufacturing, in one machine. This hybrid trend is in pursuit of improved efficiencies, aiming to shorten the process chain by reducing non-value-added time.

industrial automation company Comau.

The basic concepts of machine tooling come from the earliest days of the industrial revolution, each designed to handle a different task in the mass production process. As we enter the disruptive age of Industry 4.0, these tasks are being combined into new universal, hybrid devices with the goal of shortening the process chain, says Gérard Gousset.

Ten years ago, a five-axis machining center was a very particular machine with very specific uses, Gousset says, but today there is a growing demand for such machines even for very traditional processes.

Then there are hybrid machine tools such as combining turning and milling, or milling and additive manufacturing, in one machine. This hybrid trend is in pursuit of improved efficiencies, aiming to shorten the process chain by reducing non-value-added time.
The need for greater flexibility is also driving the trend of modular, reconfigurable machine tools. Specialist machine tools can require a significant capital investment which can be a struggle for small, nimble manufacturers looking to compete against larger rivals. More flexible modular designs, which can handle a wider variety of advanced tasks, can make for a wiser investment.

THE NEED FOR AUTOMATION

The rise of more flexible machine tools is also driven by the need for automation. While Comau mostly works with the automotive industry, machine tools with the flexibility to support integrated automated loading and unloading can reduce the footprint and complexity of the production line across the manufacturing sector, which also help shorten the process chain.
All of these efforts to blend traditional manufacturing processes within more advanced machine tools are tied to the rise of Industrial IoT, or Industry 4.0. While this is set to underpin the next wave of productivity enhancements, Gousset says it is still very early days.
Industry 4.0 is at the early phase of collecting data and is only just beginning to analyze that data in search of insight, but manufacturers are not yet experiencing its full potential for added value and foreseeing issues before they arise.

The need of the customer is not simply to collect data, the need of the customer is to improve their productivity and to reduce the breakdown of their machines – we are at the stage of early warning, or condition-based maintenance, which is the preliminary step towards the total predictive maintenance stage. Also in parallel to this is the emerging trend of applying the predictive approach to the process, in order to have predictive process control and thus improve the quality of production.

THE DIGITAL TWIN CONCEPT

The growing wealth of real-time data which can underpin predictive maintenance is also driving the use of digital twin technology which can generate a virtual doppelganger of both the machine tools and the objects they create.
Universal machine manufacturers and customers are beginning to understand the added value of the digital twin concept, such as the ability to anticipate the need for a new part and then simulate the machining of that part. We are still at the beginning of this new concept of thinking, for many managers the digital twin just seems like a fancy visualization tool but I am sure it will add much value in the future.
Meanwhile, the changing nature of European economics is also driving machine tool trends. For the last few decades manufacturers have leveraged globalization in an effort to curb costs, but now the industry is looking for other ways to remain competitive and improve their bottom line.

A WISE INVESTMENT

The European trend towards nearshoring and backshoring makes Industry 4.0 a wise investment, Gousset says, as it offers new ways for manufacturers to find a competitive edge.

The trend for nearshoring or backshoring is the opposite of the offshoring trend we experienced in the last 10 years, and this shift is justifying the huge investment for Industry 4.0 – from enterprise R&D investments to government funding. One of the drivers of Industry 4.0 is to improve the productivity of manufacturing systems and to reduce the cost of production in Europe.

This desire to bring manufacturing back closer to home while remaining economical is also driving demand for more flexible modular designs which support greater automation while reducing the footprint of the production line.
At the same time, Gousset says another machine tools trend is the growing demand for ease of use, reflecting the changing nature of society and the modern workforce.

The combination of higher employee turnover and more rapid advances in technology requires machine tools which demand less training and experience to operate than in days gone by.

ABOUT THE AUTHOR

Adam Turner

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Mechanics of helically-wound cables

Generally, helically wound cables are made up of a straight core that is surrounded by multiple layers of helical wires. These type of systems are mainly used in overhead power transmission lines, as hoist ropes or as cables in cable stayed and suspended bridges. Analysis of this cable system is crucial as it enables one to obtain effective stiffness of the cable under conditions of tension, bending and torsion. The semi-continuous model type where each layer of the helical wire is treated as a transversely isotropic continuum has been widely employed for such analysis. Unfortunately, this technique has an underlying drawback in that it becomes quite cumbersome to get the effective elastic moduli when the discrete wires are treated as a continuum and incorporating intrinsic interface conditions into the model. Alternative continuum theories have been developed, specifically for the fiber-reinforced material, but are yet to be incorporated in the analysis for simultaneous tension, torsion and bending of helically wound cables.

Dr. Loïc Le Marrec, Mr. Dansong Zhang, Professor Martin Ostoja-Starzewski from the Department of Mechanical Science and Engineering- University of Illinois at Urbana-Champaign developed a new model for the simultaneous tension, torsion and bending derivation of helically wound cables in a Timoshenko beam formalism. They purposed to employ a rod formalism instead of solving 3D equations for elasticity so as to obtain the solutions more easily and explicitly. Their work is currently published in the research journal, Acta Mechanica.

To begin with, the researchers assumed that a helically wound cable could be treated effectively as a 3D solid rod continuum that obeys Spencer’s constitutive law. Next, they employed the Timoshenko beam assumption where the cross section of the helical material was assumed to remain rigid during deformation. They then proceeded to obtain the cross-sectional forces and moments by integrating the stress components over the cross section. The researchers obtained the rod constitutive relations that relate the cross-sectional forces and moments to the rod deformations. Eventually, the applicability of the model to helically wound cables was verified.

From the numerical testing undertaken, the authors noted that by inclusion of C_F (a representation of the coupling between tension and torsion, as well as between shearing and bending) and CT (a representation of the difference between shear and torsional rigidities) in the model was essential for the correct description of the vibration of helically wound cables. The researchers also observed that when all parameters were included, the error between the measured and estimated Eigen frequencies was minimal. Moreover, it was numerically verified that with a proper set of α_i’s chosen, the lay-angle dependency of the parameters E, G, C_F and C_T derived for a circular solid rod with uniform lay angle could be applied to the 1 + 6 cables except a shift imposed on shear anisotropy (C_T).

The Loïc Le Marrec and colleagues study has presented a novel technique to describe the tension, torsion and bending of helical-fiber-reinforced rods. In this work, a full set of non-dimensional equations for the free vibration of the rod, in the form of tension, torsion and bending, has been derived. Altogether, the study has demonstrated that once the parameters for the rod model are obtained, vibrations of cables of arbitrary lengths and boundary conditions can be solved directly from the rod vibration equations and analytical solutions may be acquired that explicitly describe the behavior of helically wound cables, bypassing the need of solving equations of 3D elasticity.

About the author

Loïc Le Marrec, is assistant professor in Mechanical Science in the University Of Rennes 1.

About the author

Martin Ostoja-Starzewski is Professor of Mechanical Science and Engineering at University of Illinois at Urbana-Champaign, USA.  

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