Displaying items by tag: acelli paper

Last February 28, at the Chinese plants of SUNSHINE New Material for Hygiene and Health Care Jiangyin Co. Ltd. Located in Jiangyin, two machines for Spunlace product, a winder and a rewinder installed on two different lines side by side, have been started up.

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A.Celli supply, specifically tailored to the specific needs of the customer, includes:

  • E-WIND® STREAM Master Roll winder of 3600 mm capable of handling reels up to 2500 mm in diameter, with basis weights ranging from 30 to 100 gsm and with a maximum operating speed of 200 m/min, specifically designed for carded products and to guarantee maximum reliability and minimal maintenance
  • E-WIND® RAPID off-line slitter rewinder of 3600 mm, calibrated for reels with a maximum diameter of 1200 mm, with basis weights ranging from 30 to 100 gsm and with an operating speed of 800 m/min. Among the optionals we can find the "DSS" (defect stop system), a system able to monitor any defects on the reel, report them and give the possibility to remove them if necessary, and the “Slittomatic®”automatic slitting units positioning.

Once again, the long-standing expertise and experience of A.Celli Nonwovens and the particular attention to the customer have made possible the success of the project for the Chinese group SUNSHINE New Material for Hygiene and Health Care Jiangyin Co. Ltd.

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A.Celli Nonwovens SpA is honored to continue the fruitful collaboration with Karweb Nonwovens thanks to the supply of a winding line dedicated to the production of Spunlace

Karweb Nonwovens, a division of the KARA Holding Co. and one of the major player active in the production of Spunlace and Airlaid, has renewed, after a first order made in 2016, the trust in A.Celli and its cutting-edge solutions in the nonwoven market.

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The installation and start-up of the line, which will take place in the Turkish plant of Karweb Nonwovens located in Gaziantep, are scheduled for early 2021. A.Celli's supply includes a “Stream” Master Roll winder, an off-line slitter rewinder “Rapid” with an operating speed of 800m/minute and equipped with trim suction system, a shaft handling solution with "easy core" positioning device and a finished reel handling and packaging system.

A further confirmation of the customer's trust in A.Celli Nonwovens technology, that thanks to this supply proves, as always, to be at the cutting edge of the market and able to satisfy any type of requirement with flexibility and readiness.

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A.Celli developed the Dust Removal System with the aim of removing issues caused by dust loads in the slitting area

Nowadays dust issues are becoming more and more a prime concern, especially for hygienic fabric producers, high speed spunmelt production lines and other lines sensitive to the aforementioned issues, such as Spunlace, Airlaid and Meltblown ones.

In fact, dust deposition in the slitting area may reduce the cutting efficiency, contaminating the finished product and contributing to environmental pollution. In order to reduce the dust originated by the slitting processes in the rewinding section, A.Celli designed an efficient Dust Removal System.

A.Celli Dust Reduction System

This solution can be installed on in-line slitting winders, rewinders, spooling lines and printing lines, and it consists mainly of individual suction heads positioned on the knife holder and equipped with a blower system to remove dust accumulation on the knives. Other parts of the system are the suction line, a fan equipped with an inverter and a control unit, pipes and ducts to convey dust and air to the fan and a filter for dust/air separation.

There is also the possibility to add suction nozzles over the knives to increase the efficiency of the system.

The A.Celli Dust Removal System guarantees minimized dust loads on products and winders, expanded cleaning intervals, more production hours, the reduction of maintenance activities and the extension of the machinery useful life.

Furthermore, minimizing the dust in operational areas actually supports people’s health and safety.

Contact us for a consultancy or a dedicated case study

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Big data has been a buzzword for a few years now, as computer capabilities increase and data acquisition grows.

In the manufacturing sector, industries are seeing massive increases in the amount of data coming from their production lines, thanks to Industry 4.0 technology that makes use of machines embedded with sensors and wirelessly connected to the cloud for machine-to-machine (M2M) and Internet of Things (IoT) communication.

However, along with these massive amounts of data comes the need to effectively manage them, and this links directly to the concept of data as an asset.

2020 01 28 140846Data as an Asset explained

A data point is only a number which, considered in isolation, may have no value, and the same reasoning can also be extended to an entire data set. The concept of Data as an asset that implies that data acquire value when put in relation to other data and to business operations. In other words, these data, when analyzed together, increase their total value by helping inform business and factory decisions and strategy more effectively than they could do if considered by themselves

Read more: How to set up data driven production processes in tissue & nonwovens industries

How to manage Data as an Asset

Traditionally, a tissue and nonwovens company collected data that would provide a view into the productivity and profitability of a production line. This might be data such as costs, the production volume and the demand for the product.

Now, thanks to the Industry 4.0, the companies are provided with detailed machine data (speed and tension) and environmental data (temperature and humidity).

  • The first step in managing data as an asset is to combine the traditional data with the operational ones to come up with a complete picture of the operations and the productivity.
  • The next step is to ensure that all data is accessible via a machine-and software-independent platform. This platform must provide features such as artificial intelligence (AI) and machine learning to analyze the data and recognize patterns, thanks to which the companies can enjoy fully automated adjustments to the production processes and predictive maintenance scheduling.
  • Finally, these data must be accessible to and well-managed by everyone at the company. It should be everyone’s responsibility to ensure these data are used to balance corporate operations for maximum profitability. This allows every worker at the company, from the top down, to optimize the data for their needs, while still recognizing the needs of the company as a whole.

Read more: How to manage data governance in an Industry 4.0 system

Using Data as an Asset for intelligent collaboration

With Industry 4.0 technologies and proper management of data as an asset, tissue and nonwovens companies can ensure intelligent collaboration between the production line and the converting line. Each machine on these two lines, as we previously said, will be outfitted with sensors capable of transmitting operational data in real-time, and all of these data will flow to a single platform where they can be integrated and analyzed by AI.

The advantage of this setup is that the AI will be able to detect anomalies and small changes in the operation of any single machine or one of its part that might disrupt the flow of production and converting.

An example might be when the master roll rewinder is not moving at a speed fast enough to accommodate the rolls coming off the production line. The data will reflect this inconsistency and the speed of either the toilet roll rewinder or the production line will be adjusted automatically by the AI program.

Another example could be when there is a faulty part in the paper log cutter, resulting in the need to take the converting line offline. The data analysis will result in the automatic redirection of the roll coming off the production line to a functioning converting line.

Read more: How to measure tissue and nonwovens mill machinery performance with real time analytics

A.Celli Digital Solutions for Data as strategic Asset

A.Celli Digital Solutions has been designed to fully and automatically manage data as an asset. This cloud-based platform provides:

  • a distributed real time monitoring system called “Machine Monitoring”;
  • a business intelligence platform called “Efficiency 4.0”;
  • a Product Passport methodology called “iREEL”. 

iREEL is particularly important when it comes to intelligent collaboration between the production and converting lines, because it provides a fully integrated framework that enables communication between the data that comes from the different machines on each line and the data coming from industrial and business applications.

Data is no longer something companies can afford to collect and store somewhere they will gather virtual dust, but they must be viewed as an asset that can be used to positively impact production and corporate operations. In the tissue and nonwovens industry, data as an asset is a critical component in ensuring the smooth flow of product from the production line to the converting line and the optimal efficiency of the production process.

For more information about one of the best Industry 4.0 solution that can boost productivity on your tissue and nonwovens production line, download our free eBook "A.Celli Digital Solution: Your Fellow Traveller on Your Journey Through Industry 4.0"!

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A.Celli Group is pleased to announce that Eng. Fabrizio Tonello has been appointed to the technical management of A.Celli Paper with effect from January 7, 2020.

As Technical Director (TD), Tonello will be in charge of managing the technological development, identifying and implementing new product strategies and market opportunities, sharing the already started digital transformation process of the commercial offer of A.Celli Paper S.p.A.

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Eng. Fabrizio Tonello has a Nuclear Engineering degree from the Polytechnic of Turin and has gained many years of experience in the tissue and paper sector, covering key roles in the staff of important industrial companies such as PMT Italia Srl and Beloit Corporation.

 “I am sure that Fabrizio will be able to carry out this task in an excellent way, guaranteeing the quality of project management and the achievement of the business objectives.” says Mario Fazzi on behalf of A.Celli Group.

We welcome Fabrizio aboard and wish him to achieve great goals together with the A.Celli Group Team.

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Artificial Intelligence (AI) is the ability for a machine to take in information, analyze it and come to conclusions based on that analysis, and it is taking the world by storm. The idea behind AI is that we can program a machine to mimic the learning and decision-making capability of humans, therefore allowing us to automate processes.

AI has many applications nowadays, such as:

  • speech recognition;
  • facial recognition;
  • medical diagnosis;
  • automated customer support;
  • machine learning and deep learning

The AI global market share is expected to reach nearly $170 billion by 2025 and this technology is being adopted by numerous industries, including:

  • healthcare and medicine;
  • education;
  • human resources;
  • marketing;
  • finance;
  • retail and eCommerce;
  • public relations;
  • manufacturing.

Industry 4.0 How deep learning can help you recognize paper and nonwoven machine defects

According to a McKinsey survey, 47% of respondents say they have incorporated at least one AI capability into their business operations. Within the manufacturing sector, AI, specifically machine learning, is being used on the factory floor. In particular, it has specific and impressive application when it comes to machine operations and maintenance.

Deep learning: how it works

Deep learning is a subset of machine learning. The latter uses an algorithm to analyze data, detect patterns in those data, learn from them and adjust processes and operations accordingly, without the need for human intervention. Usually, machine learning requires a structured and labelled data set to use as a reference for the analysis, and this is referred to as supervised machine learning. However, this poses limitations, which include the tediousness of labelling data, data bias, and difficulty in transferring what is learned in one situation to another.

When it comes to Deep Learning, these limitations are minimized because this is a form of unsupervised machine learning that does not require a structured and labelled reference data set.

While both types of machine learning are useful in an industrial setting, Deep Learning is particularly useful when it comes to exploring raw data and making inferences that will reveal hidden structures within those data, and this is highly relevant when it comes to machine operations on the tissue and nonwovens production line.

How deep learning is used to identify machine defects

On the production line, machines operates around the clock and under extreme pressure, and obviously they experience wear over time that can easily result in unexpected breakdowns and idle times that negatively impact production.

Read more: 4 Tools for Tissue and Nonwovens Machines to Reduce and Optimize Idle Times

This loss of productivity can, in turn, seriously impact profits. However, until now, workers on the production line had no way of monitoring machinery at a detailed level during operations. Getting close to machinery when it is working poses a safety risk and many critical machine parts are not within the line of sight of workers.

Thanks to Industry 4.0, smart machines outfitted with sensors that transmit real-time operational data over the cloud are becoming increasingly common. Hundreds, even thousands of data points flow in every minute and these data are received by a machine-and-software-independent platform, where the data will be integrated and analyzed thanks to machine learning.

It is important to understand that the data that flows in are chaotic and raw. Deep Learning can take these data and separate them into layers that forms the structure of the neural network, such as the input layer, hidden layer, and output layer. Deep Learning neural networks can analyze the data over time to map the degradation of machine parts and machine function and determine when any machine part is coming close to the end of its lifecycle.

Subsequently, predictive maintenance can be scheduled such that a particular machine can be taken offline at the most advantageous time. This will ensure that operations will continue to run smoothly and at optimal levels without abrupt interruptions.

Deep learning for better tissue and nonwovens machine productivity

Minimizing machine downtime is one of the most important factors to ensure that tissue and nonwovens production lines remain at optimal levels of operation. Deep learning is an AI tool that is leading the way in the detection of machine defects that are not visible to workers on the production line. These defects can be caught in time to schedule predictive maintenance in order to avoid unplanned machine idle times and loss of profit.

For more information about how AI, deep learning, and automation can improve productivity on your tissue and nowovens production line, download our eBook “5 Industry 4.0 Tools that Boost Productivity in the Tissue Paper and Nonwovens Industry”!

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The Chinese group Shan Don Sun Honghe Paper Industry Co., Ltd. has purchased three more A.Celli E-WIND® P-100 Rewinders, this time for the subsidiary Sun Paper Savannakhet Co., Ltd., for a project in Laos located in Xepon, province of Savannakhet.

The almost twenty-years partnership between this important Chinese group and A.Celli Paper is further strengthened.

The three E-WIND® P-100 Rewinders will handle Medium Liner Board rolls, 6730mm wide.

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Two Rewinders will be positioned downstream of a first Paper Machine that produces paper (basis weight 140-250 gsm), while the third Rewinder will be placed at the service of a second line that produces paper, whose basis weight is 100-160 gsm.

All these three Rewinders have a design speed of 2500 mpm and are equipped with unwinders in-line to the Paper Machines, Automatic Spool Storage and new Slittomatic® Web-in cutting systems.

This order follows the one of the Rewinder sold at the beginning of the current year for the Shandon plant, already started-up and producing for several months.

The customer has also involved A.Celli Paper in some upgrades on the slitting groups of Rewinders supplied in the past: this type of activity will allow the Chinese group to obtain a higher efficiency with the relative modernization of its machinery.

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There are many tools in the modern digital age capable of increasing the efficiency of businesses operations, personalizing the communication with workers and customers and ensuring an advanced and streamlined interaction between humans and machines. Two of the most recent tools to be adopted by the manufacturing industry are chatbots and augmented reality (AR).

How Chatbots and Augmented Reality work

Industry 4.0 Chatbot and augmented reality are the future present of industrial maintenanceIndustry 4.0 Chatbot and augmented reality are the future present of industrial maintenanceChatbots are communication softwares that allow the interaction between man and machine by using natural language thanks to a so-called conversational interface, eliminating the need of interaction through programming languages. These softwares are therefore able to understand users’ questions and respond accordingly.

Augmented reality is a technology that allows workers, thanks to the so-called overlay, to “enhance” the real world field of view by superimposing data, information, and diagrams onto it by using smartphone and tablet displays or wearable devices such as head-mounted displays (HMD).

The role of Chatbots and Augmented Reality

The chatbot market is expected to reach a staggering $1.25 billion worldwide by 2025. Chatbots have been used until now usually for customer support, allowing companies to connect more easily with clients 24/7, but they can also be used by the manufacturing sector to:

  • manage supplies and inventory;
  • aid with order fulfilment and delivery;
  • simplify supply chain communications;
  • enable maintenance crews to check the conditions of machinery and equipment in the workplace;
  • facilitate maintenance crews operations.

The augmented reality market is also booming and is expected to grow to nearly $19 billion worldwide by 2024. This technology is being used to:

  • train plant workers;
  • improve worker productivity during machine installation, monitoring, and troubleshooting by providing them with real-time information so they can make adjustments/changes as they work;
  • improve the product design process by providing a visualization of the product in context and collaboration between parties that are separated geographically;
  • facilitate inspection and maintenance.

As we can see the many uses of chatbots and augmented reality can help a company significantly improve overall operations, product quality and, ultimately, profits.

Chatbots and AR in Industrial Maintenance: the main benefits

These two technologies allow workers to gather information quickly and test maintenance scenarios, all while working directly with the machine. The benefits of using chatbots and augmented reality in industrial maintenance are many, including:

  • fewer human errors;
  • faster execution of maintenance and repairs;
  • fewer machine breakdowns;
  • less machine downtime;
  • reduced maintenance costs;
  • improved operational speed and productivity;
  • better regulatory compliance;
  • higher profits.

With that in mind, let’s take a closer look at how chatbots and augmented reality can achieve these goals.

Chatbots and AR for Tissue and Nonwovens Production Line Maintenance

Like we said in previous articles[1], thanks to Industry 4.0 the machines on the tissue and nonwovens production lines can be outfitted with dozens, even hundreds of sensors that are constantly transmitting operational data in real-time.

When wearing or using augmented reality devices, maintenance workers can have the data coming in from the machinery overlaid on their field of view. These can be environmental data, such as temperature and pressure, and machine-specific data, such as speed. Thanks to this interactive information, workers can identify operational errors and faulty parts and plan a predictive maintenance schedule that will help minimize machine breakdown while keeping them operating at optimal efficiency. They can also spot problems on the production line that need to be dealt with immediately, before they cause a disruption to production.

Read more: 4 Tools for Tissue and Nonwovens Machines to Reduce and Optimize Idle Times

Chatbots support augmented reality by allowing workers to ask for information for a specific machine, such as the availability of a required spare part or access to the operating manual to determine the best course of action for repair. The information requested will be displayed via augmented reality.

Integration is the Key

The integration of data is a key element to ensure a fully operational system of industrial maintenance is in place. To achieve this, the company needs a machine-and software-independent solution capable of gathering the data from every machine on the production line. These data will be integrated, analyzed and then displayed on a computer, mobile device, or augmented reality device, allowing the remote operation of a production line and an efficient maintenance process.

Read more: Cloud Computing and Integration with Machine and Corporate Applications

Chatbots and AR are here to help you boost productivity

Companies within the manufacturing sector need to bring their technological presence to the next level to survive in today’s competitive climate. Ultimately, Industry 4.0 technology, combined with chatbots and augmented reality, will help tissue and nonwovens companies remain competitive by obtaining high quality products while reducing costs.

For more information about the various tools capable of boosting productivity on your tissue and nonwovens production line, please take a look at our eBook “5 Industry 4.0 Tools that Boost Productivity in the Tissue Paper and Nonwovens Industry”!

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In today’s world consumers want to know if the companies they do business with are acting in a sustainable manner. In addition, the environment is teetering dangerously close to the point of no return when it comes to carbon emissions, and manufacturers are increasingly expected to reduce waste and energy usage, while making the highest quality products possible.

This is a tall order, but it is one that every company within the manufacturing sector must meet, including the tissue and nonwovens ones.

One of the issues that has to be addressed to achieve our objective is the loss of productivity on a production line, and one of the top reasons for this is machine idle times.

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What is Idle Time

Idle times occur when a machine is unproductive for reasons that are outside of the control of workers or management. During this idle time, workers are generally waiting while a machine is being serviced or it is offline, and the production can continue only if the idle machine can be bypassed.

Impact of machine Idle Times

When machinery on the production line is idle, the cost for a factory is between 5% and 20% of its productivity capacity. Not only that but an estimated 80% of industrial facilities are not able to accurately estimate the scope of their machine idle times.

It is common for facilities to underestimate the cost of these machine idle times by as much as 200% to 300%, and when it comes to meeting production targets and profit margins this is unacceptable. The starting point for a tissue and nonwovens plant is to gain an understanding of their machinery and what causes idle times to occur.

Causes of Idle Times

Idle times can be either planned or unplanned. The former are generally for regular machine maintenance, software and hardware upgrades, inspections, and anything else required for the upkeep of the machine, while the latter are are generally due to machine breakage or malfunction, software or hardware errors, or overall poor performance. It goes without saying that unplanned idle times are costly and obviously more disruptive because they can cause significant interruption to productivity. 

According to the American Productivity and Quality Center (APQC) unplanned idle times are responsible for a loss of between $0.40 and $1.20 for every $20, and it is therefore vitally important for every manufacturing company to avoid these phenomena.

Reducing and Optimizing Machine Idle Times: 4 key tools

The Industry 4.0 technology is the answer to these problems.

Industry 4.0 has brought machine communication and automation to a point at which data can be collected from every machine of the production line in real-time and subsequently analyze these data in isolation or in relation to those coming from every other machine.

Read more: How to measure tissue and nonwovens mill machinery performance with real time analytics

To accomplish this, there are a number of tools that tissue and nonwovens companies need to have in place.

1. Machine Sensors

Each machine on the production line will be equipped with numerous sensors in order to collect data in real-time during operation. These data will reveal, for example, the operating state of the machine, its speed, vibrations and other environmental factors, such as temperature and humidity, that the human senses cannot detect.

2. The Cloud

Thanks to Cloud computing, the various machines will be connected wirelessly to each other, as well as to computers and mobile devices used by workers on the production line and in head office. This will allow for the remote collection and analysis of data from any production line in any plant.

Read more: Cloud Computing and Integration with Machine and Corporate Applications

3. Software/Platform

The data that are sent across the cloud will need to be integrated into a single platform capable of analysing them and to allow both a bird’s eye view of the production line and a closeup view of the operation of any individual machine.

This data integration is incredibly important in light of the fact that the machines on production lines tend to have their own unique software, isolating their data from those of the other machines and from every other data related to business operations. 

4. AI/Machine Learning

Finally, artificial intelligence and machine learning will be capable of analyzing the data coming in, recognize anomalous ones and act accordingly. Machine learning will use algorithms to understand anomalous readings and to schedule predictive maintenance. These tools are key in improving machine performance and reducing unplanned idle times or avoiding it altogether.

Reduce Idle Time and Boost Productivity with Industry 4.0

We have seen that, despite the pressures to which companies are subjected, there is nowadays a technology capable of minimizing or eliminating machine idle times.

Thanks to these tools you will be able to gather all the data sent by disparate machines in any production line, integrate them, analyze them, interpret those analyses, and implement automated measures to ensure machines are always running at peak efficiency.

For more information on how to keep your tissue and nonwovens production line operating at peak efficiency, download our free eBook “5 Industry 4.0 Tools that Boost Productivity in the Tissue Paper and Nonwovens Industry”!

Published in European News
Friday, 29 November 2019 09:32

A.Celli - 24/7 Assistance

A.Celli Group has always guaranteed continuous and immediate assistance to its customers with a free of charge 24/7 service

The A.Celli Group provides its customers with various access channels to request assistance: in the first instance, in case of emergencies, contact can be made by telephone, using a dedicated H24 number, for real time solutions; there is also a dedicated e-mail address, accessible directly or via website and, finally, the chatbot, on the A.Celli website too.

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If the problem is solved by phone, the technician who took charge of the request will trace the event, indexing it with various references, so that it remains memorized and usable for the data entered, both for use by the supplier company and by the customer.

If, on other hand, the problem cannot be solved immediately, the customer is asked to open a "ticket" on A.Celli website. This procedure generates an email that is automatically sent to the Customer Care team in charge of assistance. Also in this case, from taking charge of the request, up to the solution of the problem, the intervention is traced: in this way an archive of cases is created with relative operations and resolution times, which can be consulted afterwards and which provides important data for the development of predictive maintenance (in the field of Industry 4.0).

Every A.Celli machine is connected to the web via VPN: this connection allows remote access to the machine data (remote assistance). Using the VPN, the dedicated team verifies the solvability of the problem: generally it is possible to take action on software anomalies or regulation, solving the same and restoring the optimal activity of the machine.

If, instead, it is deduced that the problem is of mechanical or process type, a technical on site intervention by our specialists becomes necessary.

Recently the A.Celli site has been implemented with a chatbot which, once activated, allows the identified customer to request the Customer Care service, specifying which of the two companies he wishes to interface with (A.Celli Paper or A.Celli Nonwovens) and choosing the way in which to be contacted by the assistance team. Also in this case a "ticket", which will trace the whole solution path, will be opened.

Summarizing, A.Celli customers can always count on Customer Care services, managed by skilled and experienced technicians:

  • Telephone assistance and emergencies 24/7
  • Chatbot
  • Ticket opening (assistance request)
  • Teleservice VPN
  • On-site technical interventions
  • Process supervision
  • Training programs
  • Safety analysis of the machine
  • Technical documentation
  • Worldwide local assistance
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