2022
Smart Industry – April 2022 – Product News: Software AG’s TrendMiner NextGen. TrendMiner, a Software AG company, has launched what it touts as the next generation production client for industrial analytics. TrendMiner NextGen, the 2022.R1 release, provides a seamless user experience, per its maker, enabling an extended pool of operational experts to make data-driven decisions and optimizing the performance of their operations to meet business, environmental, and safety ambitions. Continue reading…
Globe Newswire – April 2022 – Software AG’s TrendMiner Latest Release Enables an Analytics-driven “Production Cockpit” for Process Manufacturing Companies. The Production Cockpit puts engineers, operators, and management in full control of the Digital Factory anywhere on the globe
Plant Engineering – March 2022 – Predict process events with contextual data insights – Article by Rob Azevedo, product manager & strategic alliances with TrendMiner. “Maintenance teams see predicted machine failures”.
Oil & Gas Engineers – March 2022 – Predict process events with contextual data insights – Article by Rob Azevedo, product manager & strategic alliances with TrendMiner. “Maintenance teams see predicted machine failures”.
Smart Industry – March 2022 – How to use contextual insights to develop true prescriptive analytics – Article by Rob Azevedo, product manager & strategic alliances with TrendMiner. “Events must be put into context to be fully understood”.
Proccess Industry Informer – March 2022 – In this article, Wouter Daniels, Data Analytics Engineer at TrendMiner, shares how to achieve sustainable process operations through advanced Analytics. Most process manufacturers already collect data from sensors throughout their plants. Yet, their process experts struggle to understand the data, which could be used to achieve a variety of operational improvements
Plant Engineering/Control Engineering – Feb 2022 – In this Digital Transformation ebook, you can learn more about LANXESS digital transformation journey and how TrendMiner is supporting it. Software AG CEO Sanjay Brahmawar and LANXESS CDO Jörg Hellwig talk about Data, Business, Digitalization, and important self-service tools such as TrendMiner, to enable better manufacturing process data analysis and the optimization of their plants.
Pharma Manufacturing – January 2022 – Data-driven quality control for vaccine production – From the onset of the COVID-19 pandemic, the race to produce a safe and effective vaccine was underway. Less than a year later, authorized vaccines began being administered, and now, as of this writing, nearly 10 billion doses have been administered across 184 countries. The development, testing, and production of a new vaccine happening in the span of one year is something the world had never seen, and something that could not have been possible without digital technologies.
Smart Industry – January 2022 – Data analytics: A case for growing analytics maturity – Companies in the process-manufacturing industries have been capturing process data for years, storing it in their historians. But how do you reach the full potential of this data to improve operational performance?
Process Industry Informer – January 2022 – Achieving Sustainable Operations through Advanced Analytics – Most process manufacturers already collect data from sensors throughout their plants. Yet, their process experts struggle to understand the data, which could be used to achieve a variety of operational improvements.
Control Engineering – January 2022 – Spreadsheets for analytics – Many companies offer software for data analytics to create information and insights from data collected from automation, controls, and instrumentation. Most data-gathering software also downloads in a spreadsheet format: Many users have spreadsheets for special applications or quick insights.
2021
Featured: Pharmaceutical Processing World – May 2021, by Michael Chang: Improving vaccine production with advanced analytics. The rise of Industry 4.
0 and the use of digital technologies like automation, computer science, and self-service analytics have helped pharmaceutical companies to deliver COVID-19 vaccine efficiently and control product quality during production. Read how Self-service Industrial Analytics contributed. This article was also published in Plant Engineering and Control Engineering.
RT Insights – September 2021, by Niki Driessen: Data Lakes, Time-Series Data, and Industrial Analytics. The challenges of integrating time-series data into data lakes can be overcome by using the right architecture and providing the appropriate metadata.
Plant Engineering – May 2021, by Michael Chang: Data-driven decisions improves COVID-19 vaccine production. This article shows a great example of how self-service analytics really delivers on its worth and drives process optimization. COVID-19 vaccinations are helping to save lives and to return life to normal. Without self-service analytics, vaccination production could never have met the targets needed to protect and save lives and get society back on track. Download PDF.
Water Technology Online – June 2021, by Daniel Münchrath: Cover Story – Facing Industrial Water Challenges Head-on with Advanced Analytics. New advanced data analytics technology can help analyze, monitor and predict treatment processes to provide a holistic plant overview. The article includes some real-world practical use cases.
– Watch the video interview – Daniel joins Water Technology editor Daniel Gaddy to discuss the issues shaping analytics and IIoT adoption for the industrial water sector
Process Heating – June 2021, by Nick Petrosyan: “Analytics can Improve Operational Performance”. Eliminating data silos and incorporating contextual data with process data enhances operational understanding and transparency for the process engineers. This article include the following practical advanced analytics use cases:
- Cutting Energy Consumption at a Reverse Osmosis Plant
- Sticky Valve Identification and Monitoring
And the article discusses how to use self-service industrial analytics for Predictive Maintenance of critical and non-critical assets.
Automation.com – May 2021, by Daniel Münchrath: How the Process Industry Can Use Advanced Analytics to Manage Its Water & Energy Challenges. Industrial water and energy must be properly and carefully managed to ensure asset reliability, reduce carbon footprint, comply to environmental regulations, and ensure efficient and economic production processes. A solution for these challenges is to empower process engineers with advanced analytics.
Oil & Gas Engineering – May 2021, by Julian Pereira: Self-service analytics support asset reliability and operational performance. The key to reveal opportunities to reduce costs, waste and emissions, as well as improve operational and personnel efficiency and safety is making sure the entire team of process experts and engineers have access to the data and have the right tools to analyze it. Read this article with case study examples demonstrating real world value, like:
- Avoid unexpected flare flow problems
- Compressor trip diagnosis
- Improving sulfur recovery units
Processing Magazine – May 2021, by Nick Petrosyan – Going Beyond the Data: How Self-Service Analytics Plays a Critical Role in Communication. Self-service Industrial Analytics goes beyond the analytics and allows for effective communication and knowledge-sharing on both a local and global level.
“Effective communication is key for any industrial manufacturing process. And it plays a vital role in delivering a quality product to the customer. On the other hand, lack of communication causes many disruptions and problems.” – Product Engineer – Kuraray Americas.
Water & Wastes Digest – May 2021, By Daniel Münchrath – Securing Water for Our Future. 
Water is one of the most essential requirements for life. We cannot live without it, so we must protect what we have. Advanced Industrial Analytics offer substantial optimisation potential for water treatment plants to secure it for our future. In this article you find real life use cases for water treatment plants.
Chemical Engineering – May 2021, by Michael Chang – Advanced Analytics for Process Safety. A look at how advanced analytics facilitates and improves process safety efforts within the chemical process industries (CPI). Simply by the nature of some of the chemicals used and the associated complex processes involved, chemical plants can be hazardous. Process engineers can help improve plant safety using sensor-generated production data. The article includes real life use cases.
Forbes – April 2021, By Thomas Dhollander – Data Lakes are on the Rise. Big players like Microsoft and Amazon offer inexpensive cloud-based solutions for organizational data storage known as data lakes, which are rapidly becoming a central component in the cloud strategy of many CIOs. The promise of these data lakes is significant, but a data lake can quickly deteriorate into a data swamp, where users struggle to extract the right data, performance is insufficient and organizational expectations aren’t met.
Indian Chemical News – April 2021, by Mike Malone, Process Engineer, Toray Plastics – A Day in the Life of a Process Engineer: Looking Back and Looking Forward with Self-Service Analytics. 
In nearly 26 years of process engineering work at Toray Plastics (America), with almost 20 of those years in direct support of manufacturing, working on rotating 12-hour shifts, my team and I have faced and have overcome many challenges. When I was asked about my thoughts on what “a day in the life of a Process Engineer” is like, I had a chance to reflect on the main challenges I encounter on a day-to-day basis. I boiled it down to these three important areas: Communication, Process Control Management, and Data Analytics.
This article was also published in Process Industry Informer – March/April 2021 – A Day in the Life of a Process Engineer.
Processing Magazine – Feb 2021, by Nick Van Damme – Growing Your Analytics Maturity. 
For a closer collaboration between Process Experts and Data Scientists, modern self-service industrial analytics tools allow notebook integration and data model deployment for the wider operational teams. Read how embedded notebooks enable process data experts to solve up to 95% of the operational use cases.
Water Technology – Feb 2021, by Ruchika Tawani and Daniel Münchrath – Water 4.0: Reducing Energy Consumption with Advanced Data Analytics. Water reuse and wastewater treatment are intrinsically energy intensive. They require moving large volumes of water with pumps and electric motors followed by treatment to meet stringent regulatory requirements. In conventional wastewater treatment plants (WWTPs), aeration is one of, if not the biggest, energy consumers in this process. Other significant energy consumers include filtration and disinfection processes. It is clear, however, that the industry must take serious steps in reducing the amount of energy it uses. Read how self-service advanced analytics can help reduce the energy consumption.
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2020
Smart Manufacturing – Dec 2020, by Thomas Dhollander: LANXESS prospers as it lets analytics do the driving. A true smart factory uses all the data available, in combination with human expertise to improve business outcomes. This requires democratization of data and analytics. Read the article to get inspired by LANXESS.
Hydrocarbon Engineering – Dec 2020, published by Callum O’Reilly and written by Julian Pereira: Meeting decarbonisation targets. Process manufacturers are facing unparalleled challenges in 2020 in terms of maximising business reliability and profitability. Additionally, for organisations to establish sustainable climate strategies and meet de-carbonisation targets along with increasing competitive operational performance and resilience, they will need to incorporate accelerated digital transformation as a significant factor in their business strategies. Read how advanced analytics can help meet the targets.
Pharma Manufacturing – Nov 2020, by Fréderick Motte: Democratizing analytics for next generation maintenance. The road to prescriptive maintenance starts with improved asset reliability. A fully artificial intelligence led prescriptive analytics system for running an autonomous factory is still a bridge too far today. However, organizations can start by improving the reliability of their asset performance. Self-service industrial analytics can bring asset reliability to the next level, notifying operational specialists early with instructions and thus helping to increase overall profitability and plant safety.
Petroleum Economist – Nov 2020, by Julian Pereira: Digitalization Review 2020. Operators at a higher stage of digital maturity have been better able to endure the economic crisis. Businesses at a lower level of digitalisation have been made aware of the importance of overhauling legacy working practices. Ambitious decarbonisation pledges have also highlighted the industry shift towards greenenergy. Digitaltechnologies can help play a crucial bridging role towards this netzerofuture, driving operational efficiencies and lowering operational emissions.
In this digitalisation report, industry experts examine the changing cybersecurity landscape, automating #refineries, the power of the digitaltwin, extending offshore asset life, among many other topics.
Download this free resource here https://bit.ly/2UXyBlc
Chemical Processing – Oct 2020, by Edwin Van Dijk: Specialty Chemicals Maker Does More with Data. Specific steps foster the success of global roll-out of advanced analytics. Read why LANXESS choose to roll out self-service advanced analytics and how they addressed the global roll-out challenges.
Pumps & Systems – Oct 2020, by Edwin van Dijk: Pumping Self Service Analytics for Greater Value. Real-time monitoring can alert users to issues and process failures. Increasing financial flexibility to safeguard against commoditization can be obtained by getting as much out of existing production capacity as possible, and one way to do that is by applying advanced analytics to individual, yet critical, assets such as pumps. The people managing those types of assets who have begun to understand the importance of embracing new technologies stemming from the rise of Industry 4.0 are realizing the value that digitalization can bring when they are fully able to leverage the volumes of data at their disposal on their own, without the need for a data scientist.
Processing Magazine | Maintenance & Safety | Asset Management – Oct 2020, by Tommy Peters: Realizing your smart factory’s full potential with self-service advanced analytics. With the use of self-service analytics, process manufacturers can quickly turn their factories into smart factories, which will allow them to leverage the full potential of data and analytics.
Automation.com, a subsidiary of the International Society of Automation (ISA) – Oct 2020, by Nick Petrosyan: Specialty Chemical Production: Advantages of Batch Analytics. The chemical industry is currently going through turbulent times due to COVID-19. Market demand has shifted greatly and production levels may have been impacted negatively or in some cases even positively. In many cases, we see a rise of batch production due to more individual customer demands. Facing these turmoil times and to even come out on top of the market requires creative contribution from all employees at all levels of the organization. Data can support creative ideas or even initiate new ideas for improving operational performance in the new situation. Read the full article
Food Manufacturing – Oct 2020, by Nora Villarreal: What Does a Smart Factory Look Like? Factories that have the ability to capture, store and leverage process data (Big Data) are called Smart Factories. But what should be done with this Big Data? How can companies gain insight into this data and use it to improve production processes, team, and plant efficiency? The answer is technology and smart factories have three essential characteristics, which are explained in this article.
Forbes Technology Council – July 2020, by Thomas Dhollander: Analytics for Operating in the New Manufacturing Normal. Recently, many process manufacturing companies have started or are progressing with their digitalization journeys. But due to the Covid-19 pandemic, many of them are facing a new truth. Some companies have accelerated their production, others have modified their product lines and a third group have had to stop production due to lack of demand. In this article Dhollander explains how, in the new manufacturing normal, making a digital transformation is mission-critical.
Oilfield Technology – July 2020, by Nicholas Woodroof, Assistant Editor: Data analysis softens the impact of current crisis. Julian Pereira from TrendMiner explores how the use of data analytics can help Upstream Oil & Gas companies move to next levels of operational excellence and face volatile market pressures. Self-service industrial analytics shows rapid adoption and an increasing array of use cases. In this article some upstream cases engineers have worked on are discussed:
- Well surveillance and optimisation
- Offshore compressor monitoring
- Unexpected flare flow issues
Profood World – June 2020, by Jeanne Schweder: By Seeing Patterns, Analytics Software Models Improve Process Control. Translating raw data into usable information has been a difficult task for industrial companies. Using TrendMiner, a self-service industrial data analytics software, Sitech was able to overcome this problem. Sitech’s approach and lessons learned can inspire food processing companies.
AutomationWorld – June 2020, by Jeanne Schweder: By Seeing Patterns, Analytics Software Improves Process Control. Translating raw data into usable information has been a difficult task for industrial companies. Using TrendMiner, a self-service industrial data analytics software, Sitech was able to overcome this problem. Read the full digitalization journey and the success Sitech achieved:
“Adapting to new software like TrendMiner often asks for an organizational shift: a new way of looking at technology and data. It enforces alternative thinking and a new way of looking at operational performance using data,” says Marc Pijpers, principal process control engineer at Sitech.
Plant Engineering – May 2020, by Edwin van Dijk: Introduce analytics into industrial environments. Put analytics in the hands of the process experts who understand the data best. | What is the best way for a company to collect and analyze the data needed to make data-driven decisions that support good business outcomes? Let’s look at some of the best ways to successfully implement advanced analytics for multiple operational stakeholders.
Control Global – May 2020, by Jim Montague: Cornerstone cracks the data analytics case. | End users are using faster, more capable analyses to make better decisions and optimize operations. Aubyn Chavez, process improvement engineer, Process Improvement Group, Cornerstone in Waggaman, La., near New Orleans advises that software like TrendMiner can enhance or accelerate process knowledge. She proves her point with a few practical use cases and concludes with: “Analytics software is better than spreadsheets because it lets us work faster by highlighting process details better and lets us disprove our traditional prejudices.”
Forbes Technology Council – April 2020, by Thomas Dhollander: Data Scientists Or Self-Service Analytics? Discovering A Winning Approach To Manufacturing Analytics | Today’s manufacturing companies are investing significantly in analytics as part of their digital transformation programs. But analytics is a broad topic on its own, with many different factions and beliefs, and many companies are struggling to understand which approach is the better one. In this post, we’ll focus on two conflicting approaches: the belief that the data scientist should take the lead when it comes to analytics, and the notion that the business user should be in the driver’s seat (often referred to as self-service analytics). So what is the winning approach?
Processing Magazine – April 2020, by Julian Pereira: Reduce Emissions by Improving Sulfur Recovery Unit’s Performance with Self-service Industrial Analytics | Oil & Gas companies are continuously striving to optimize overall equipment effectiveness, performance and profitability within a highly volatile and regulated environment. Several of those regulations are coming from an increasing industry effort towards the reduction of emissions that affect both health and the environment.
In this article Julian Pereira explains in detail how process experts were able to improve the Sulfur Recovery Unit’s Performance with use of TrendMiner.
Industrial Process Products & Technology – April 2020, by Edwin van Dijk: The Benefits of Utilizing Advanced Analytics in Chemical & Process Manufacturing. | Self-service analytics eliminates potential cost-intensive data models because it supports plug-and-play functionality and user-friendly interface for process experts allowing immediate value and ROI. The benefits and competitive advantage self-service analytics bring to a process manufacturing company far outweighs the minimal investment needed to set it up and deploy it. The article includes a range of practical use cases from Trendminer customers.
Pump & Systems – March 2020, by Jasper Rutten, Global Advanced Analytics Manager Huntsman: Advanced Analytics Speed Up Continuous Improvement Cycle. | In many companies, operational data is still kept in separate silos, adding an extra challenge to improve operational excellence by use of advanced analytics. Through various uses cases addressed with TrendMiner, Huntsman was able to increase stable and therefor safer production as well as increasing control over the product quality. This article includes practical use cases:
- Develop a soft sensor on product quality
- Control batch processes with finger printing
- Product Quality Improvement using DMAIC
Hydrocarbon Engineering – March 2020, published by Callum O’Reilly, Senior Editor: Doing more with data | These days, there is no escaping the phrase ‘digital transformation’. There is no denying that the rise of Industry 4.0 is impacting day-to-day environments. Digital transformation is challenging traditional approaches and can open up new opportunities, if the willingness to adopt is there.
Forbes Technology Council – March 2020, by Thomas Dhollander: Considerations For Analytics-Driven Decision-Making At Scale | To make analytics-driven decision-making possible at scale in an organization, the data needs to be available, accessible and digestible for users. When using a historian, many criteria are already met. The next step is to provide an analytics tool that is tailored to the needs of the users. To make a new tool successful companies must put a set of key success factors in place for enabling successful data-driven decision-making at all levels of the company. Read the article how TrendMiner customers drive for success at scale, among which LANXESS.
Power Magazine – February 2020, by Edwin van Dijk: Using Self-Service Analytics to Improve Power Plant Efficiency | There is a widespread movement to reduce carbon emissions around the world. One way to do so is by improving plant efficiency, but that can be easier said than done. However, self-service analytics could play a role in the process. Advanced technology can help subject matter experts spot areas for improvement faster and more effectively than was previously possible. Includes practical use cases:
- Increased Efficiency of a Power Generation Plant
- Control Energy Consumption within the Cooling Water Network
IIoT Connection – Published the article Using Self-Service Analytics to Improve Power Plant Efficiency in their February 2020 issue.
Industry Week – January 2020, by Petty Ferry: Seeking Digital Supremacy. LANXESS invests in added analytics capabilities in quest to become digital leader.
“Thus far, Lanxess has significantly increased its capacity utilization, optimized resource efficiency and reduced maintenance costs. The digital transformation also serves to further develop employees”, according to LANXESS CDO Jörg Hellwig. “Competences in the field of digital data analytics will be essential for chemists and chemical engineers in the future,” he says.
Processing Magazine – January 2020, by Nora Villarreal: 5 Ways You Can Improve Your Process Operations with Self-service Analytics | New platforms help process engineers make the most of their data. With real live use cases about how to:
- Reduce cost and waste
- Improve product quality and yield
- Avoid unplanned downtime
- Reduce energy consumption
- Share information across teams and shifts
Join our media ecosystem
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2019
Smart Industry – November 2019: Analytics-driven decision-making for process engineers | How efficient do you want your engineers to be? Includes use case from Arlanxeo.
Manufacturing Automation – November 2019 by Edwin Van Dijk: Power to the Process Engineer | Practical use of self-service data analytics makes process engineers more effective at improving operational performance. Includes use cases from Ashland and Covestro.
IIoT Connection – October 2019 by Edwin van Dijk: Creating an Analytics-enabled Workforce. | New self-service data analytics tools allow plants to create an analytics-enabled workforce that can readily address production issues and continuously improve processes.
Forbes Technology Council – October 2019 by Thomas Dhollander, CTO of TrendMiner: A Simple Recipe For Analytics-Driven Operational Decisions At Scale. | Manufacturing companies today understand that digitalization is required to remain a market leader and sustain future profitability. On the wave of digitalization within the era of Industry 4.0, advanced data analytics has been the primary domain of data scientists. To grow your company into the future… read more.
Processing Magazine – September 2019 by Edwin van Dijk: The Journey to Analytics-driven Production Insights | Controlling business outcomes by democratising analytics at each level of the organisation. Includes use cases from Arlanxeo and Sitech. Also published in:
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Automation.com: Democratized Analytics Guides Industry 4.0
Offshore Magazine – September 2019: Analytics software enhances real-time BOP monitoring | Deepwater Subsea has signed a two-year agreement with TrendMiner, a provider of self-service analytics solutions, to use their software within its BOP real-time monitoring service Janus 24 on multiple rigs.
Technopedia – July 2019, 10 Real-world Use Cases: AI and ML in the Oil and Gas Industry | The applications of AI and machine learning (ML) in the oil & gas industry are many, and some of them can really make the difference in a sector that is seeking to renew itself. Download the report and read TrendMiner’s use case at page 6 from Deepwater Subsea.
POWER Magazine – June 2019, by Thomas Dhollander & Nick Petrosyan: How to Monitor and Predict Operational Performance with Digital Analytics [PODCAST] | Power plants are capturing operational data in ever-increasing amounts. However, analyzing all the data can be challenging. A number of tools are available that can help. Listen to the podcast
Hart E&P – April 2019, by Edwin van Dijk: Harnessing New Technology For BOP Testing | Implementing self-service analytics not only saves time but provides greater insight. A customer success story of Deepwater Subsea, based on the interview with Deepwater Subsea’s CEO and founder Mike Fry.
Control Engineering – March 2019, by Edwin van Dijk: Connecting quality data to process data | Using advanced analytics can help assure product quality and overall operational efficiencies. See case study example. Also published in:
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Control Engineering’s 6th most clicked articles in April 2019.
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IIoT Connection: Connecting Quality Data to Process Data
Manufacturing.net – March 2019, by Edwin van Dijk: Operating in the Fast Lane | In the world of IIoT, data is considered to be the new oil. But its full potential will only be unleashed if operational context can be taken into account when analyzing, monitoring or predicting operational performance. Shedding necessary light onto time-series data through dynamic contextualization enables you to take your processes into the highest gear of operational excellence, and your organization into the future. Also published in
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Process Industry Informer, starting from page 10.
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2018
North Carolina Rural Water Association – November 2018, by Bavo Symens: Emerging Energy, Reducing the water industry’s carbon footprint with advanced data analytics, page 7-9.
Pumps & Systems – October 2018, by Bavo Symens: Use Data Analytics to Comply with HSE Regulations. How the water industry can improve energy management with new performance insights.
PlantServices – October 2018, by Edwin van Dijk: Self-service continuous improvement, Tap into advanced analytics to fuel improvement efforts across the organization.
Processing Magazine – October 2018, by Edwin van Dijk: A new approach to data-driven process improvements. How self-service industrial analytics combined with a DMAIC cycle approach can fuel continuous improvement projects.
Chemical Engineering – October 2018, by Edwin van Dijk: Improve Energy Management to Reduce Your Facility’s Carbon Footprint.
Water & Wastes Digest – September 2018, by Bavo Symens: Emerging Energy, Reducing the water industry’s carbon footprint with advanced data analytics.
Manufacturing.Net – September 2018, by Edwin van Dijk: Self-Service Analytics and DMAIC.
IIoT for Engineers – September 2018, by Bert Baeck: Use Process Analytics Efficiently, page 7-10.
Control Engineering – September 2018, by Bert Baeck: Use process analytics effectively. Pattern recognition software leverages historian data to automate information gathering and make process analytics more efficient and accurate.
ControlGlobal – August 2018, by Renzo Rondags: On the Road to a Data Driven Organisation, page 59 and 60.
ChemInfo – June 2018, by Edwin van Dijk: Reduce Carbon Footprint With Advanced Analytics-Driven Energy Management
Process Industry Informer – June 2018, by Artur Beyer: Self-service Predictive Analytics Reduces Downtime & Avoids Unnecessary Risks
Processing Magazine – May 2018, by Artur Beyer: How to Use a Self-service Predictive Analytics Approach
Chemical Processing – May 2018, by Janice Abel, ARC Principal Consultant: Advanced Analytics Proves Its Value at Total R&C, Self-service industrial analytics software speeds problem-solving and eases capturing and sharing of knowledge.
Flow Control Network – May 2018, by Janice Abel, ARC Principal Consultant: Improving Operations with Advanced Analytics or in the Online magazine on page 10
Hart E&P – May 2018, by Edwin van Dijk: Analytics-Driven Energy Management Reduces Carbon Footprint
Oil & Gas Productnews – April 2018, by Edwin van Dijk: Analytics-Driven Energy Management Aids In Carbon Footprint Reduction
Process Engineering (UK) – March 2018, by Artur Beyer: The emerging impact of batch analytics
CHEManager – March 2018, by Artur Beyer: Fine & Specialty Chemicals focus – Specialty Chemical on the Upswing
Chemical Engineering – Feb 2018: Placing Data Analytics in the Hands of Engineers
ChemInfo – Feb 2018, by Bert Baeck: Using SCADA Data for IIoT Just Became Much Easier
Control Design – Feb 2018: TrendMiner Industrial Analytics Software 2017 R2
ChemInfo – Jan 2018, by Artur Beyer: Emerging Impact Of Batch Analytics
PlantServices – Jan 2018, by Edwin van Dijk: What to watch for in automation in 2018
ChemInfo – Jan 2018, by Bert Baeck: The Route To Digital Transformation
European Rubber Journal – Jan 2018, by TrendMiner: Arlanxeo rolls out TrendMiner software to plants
PharmTech.com – Jan 2018, by editor Jennifer Markarian: Pharma Equipment Gets Smart
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2017
Rubber & Plastics News – Dec 2017, by editor: Arlanxeo rolls out TrendMiner software to plants
Specialty Chemicals World – Dec 2017, by Artur Beyer: Emerging Impact of Batch Analytics
Processing Magazine – Dec 2017, by Thomas Dhollander: Analytics awareness for the process engineer
Oil & Gas Engineering – Dec 2017, by Bert Baeck: Pattern recognition illuminates the downstream
Plant Engineering – Oct 2017, by Bert Baeck: Process engineers need new analytics awareness
Data Informed – Oct 2017, by Bert Baeck: The route to digital transformation
Process Industry Informer – Sept 2017, by Edwin van Dijk: Next generation analytics improves plant profitability
Pumps & Systems – Sept 2017, by Edwin van Dijk: Industrial Analytics – compass to navigate Industry 4.0
Computable -Set 2017, by TrendMiner: TrendMiner voorspelt industrieel onderhoud
Manufacturing – Sept 2017, by Edwin van Dijk: Compass to navigate Industry 4.0: industrial analytics
ARC Advisory – Blog – Aug 2017, by Janice Abel: Next Step: Global Roll-out of Analytics Software
Chemical Engineering – July 2017: Software improves pattern recognition, trend analysis’ with TrendMiner 2.0
Manufacturing Automation Magazine – Jul 2017, by TrendMiner: TrendMiner predictive analytics software 2.0 for process industries
ARC Advisory – Blog – Jul 2017, by Janice Abel: Total R&C rolls out TrendMiner self-service analytics globally
Chemical Processing – June 2017, by Seán Ottewell, Editor at Large: Data: Finding What’s Hiding Gets Easier
Manufacturing North America – June 2017, by Bert Baeck: Is SCADA getting easier?
Dataconomy – April 2017, by Thomas Dhollander: Data analytics is the key skill for modern engineers
Process & Control (UK) – May 2017, by Bert Baeck: SCADA & the IIoT “Making Better Use of Data is Key to Implementing IIoT”
Manufacturing.net – April 2017, by Thomas Dhollander: A New Age In Manufacturing
Pumps & Systems – April 2017, by Bert Baeck: Using SCADA data for IIoT just became much easier
ARC Advisory – Blog – April 2017, by Constanze Schmitz: Sitech @ EIF 2017 – Process Data Analytics Journey
Energy Global – April 2017, by Angharad Lock: TrendMiner launched at Total to aid reliability
OSIsoft – March 2017, by Fabrice Leclercq: Total presents on TrendMiner self-service process analytics (VIDEO)
Chemical Processing – Feb 2017, by TrendMiner: TrendMiner 2.0 expands self-service analytics
OSIsoft – Feb 2017, by TrendMiner: TrendMiner and OSIsoft sign OEM agreement to enhance integration
ChemInfo – Jan 2017, by Bert Baeck: Google For Industry: Taming Big Data
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2016
International Society of Automation (ISA) – Dec 2016, by Bert Baeck: Smarter access to analytics for engineers
Oil & Gas Engineering – Dec 2016, by Bert Baeck: Easier way to use SCADA data for IIoT
Pharmaceutical Manufacturing – Dec 2016, by Bert Baeck: Smarter Access to Analytics for Process Engineers
Oil & Gas Engineering – Oct 2016, by Bert Baeck: Data mining and analytics for performance optimization
Control Engineering – Oct 2016, by Bert Baeck: Data mining and analytics for optimization in oil & gas
Processing Magazine – Oct 2016, by Bert Baeck: The importance of data monitoring in process industries
Processing Magazine – Oct 2016, by Bert Baeck: Efficient self-service analytics for engineers and operators
Pharmaceutical Technology – Sept 2016 by Jennifer Markarian: Making use of process data (interview)
Food Manufacturing – Aug 2016, by Bert Baeck: Plant connectivity and access to assets, systems and data
Automation.com – April 2016, by Bert Baeck: Google for Industry: Taming Big Data
LNS Research – April 2016, Matthew Littlefield: Cloudera IIoT platforms and TrendMiner industrial big data analytics
Control Global – April 2016, by Bert Baeck: Self-service analytics for non-data-scientists
ARC Advisory – Blog – Jan 2016, by Peter Reynolds: TrendMiner Develops Industrial Process Analytics for the Non-Data Scientist
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If you would like to collaborate with us on an article for use in your publication, or you’d like to arrange an interview with a TrendMiner representative to discuss a particular topic, please contact us for further information.
Do you need our logo?
If you need to represent the TrendMiner brand, we will be glad to help you. To request company texts, our logo or other brand-related elements, please contact the TrendMiner Marketing team for assistance.
