According to the German Federal Statistical Office, energy consumption by the industry for the production of goods hardly changed between 1995 and 2019. In 2019, it amounted to 3,874 petajoules. This means that it remains at the same level as in previous years. Germany plans to halve its primary consumption of energy by 2050, with the industry having to take part. In the era of the energy crisis, the drive to improve corporate energy efficiency is entering a new level.
Today, many companies are looking at how they can improve their efficiency in the area of energy use, how to conduct a detailed review of their utilities to reduce annual energy consumption, and systematic monitoring of what the savings are.
Without an overall strategy for new energy management systems in manufacturing, it is nearly impossible to drive change in companies and drive global and unified initiatives for energy-saving improvements. Only a dedicated energy team supported by the entire organization can develop a strategy, conduct an energy audit and establish an energy efficiency plan to implement appropriate measures. Our approach to project implementation can help companies avoid excessive energy costs, despite rising prices.
Transparency plays a key role in manufacturing, as it is impossible to optimize something that is not visible. Through transparency, awareness can be increased and knowledge can be built, allowing for informed decisions based on data and insights.
Good visualization forms the basis of a central data source and allows for defining specific energy-saving projects. Without this step, the chance of success decreases significantly.
In today’s complex manufacturing processes, data from electricity meters is not enough. It is necessary to meaningfully correlate metering data with other information, such as data from production planning, the manufacturing facility, or the process.
Only this approach provides a complete picture and can help optimize the areas with the highest energy use in production facilities.
To improve the efficiency of energy usage, it is essential to have a solution such as an IIoT platform that provides a central source of data. The platform collects information from a variety of sources, puts it into context, and enables it to be transformed into useful designs and manufacturing processes. Drawing on our extensive experience in this field, we have developed the Energy Advisor for industry – the first step in understanding and reducing the consumption of utilities in the industry. Efficient use of utilities and becoming more energy-efficient is key to success.
This involves identifying the main consumers (SEUs) and marking their consumption capacity. It is important to record 80% of the system output. This can be done through simple data analysis, as SEUs are usually known within the company.
The knowledge available in the company is backed up by numbers, and the proof is provided to the auditor, contact person, or customer.
Not all SEUs can be optimized at the same time. Identify 5 major SEUs as a first step and implement possible energy-saving projects there. The definition of SEU should refer to physical machines and manufacturing plants, not company departments or locations – otherwise you are adding complexity without adding value. Aggregating data to a location or department can be done by the IIoT platform as needed.
Critical operating parameters are primarily those factors that can be actively managed during operation. Strict correlation is determined by regression analysis. These critical operating parameters must be defined and included in key figures and operational management. These parameters are further analyzed in regression analysis and correlated with further data.
The results of regression analysis, which take into account operating parameters, should be carefully examined for their savings potential and simulated with future consumption in mind. There are various factors that can have a varying impact on the savings potential of a given SEU.
It is important to define critical operating parameters. These are parameters that can be influenced by your employees, such as temperature or speed. These are not parameters that cannot be influenced, such as outdoor temperature or humidity. However, if these parameters play a role, systems must be designed in such a way that they can be monitored and controlled (e.g., encapsulation). Create a list for the manufacturing plant being analyzed and list the parameters that can affect it. The data analyst can then search the database for correlations and provide quick results. Prioritization of influencing parameters is not done at this stage.
The method of analysis by linear regression is a procedure to find a description of a variable y as a linear function of other variables (minimum of one – x) t.i.e. y=f(x). Thus, linear regression can be used to describe the dependence of the expected variable y on the variables linearly independent of it. Thanks to this, we can recognize with which parameters the predicted variable correlates, and even extrapolate the set to predict values, and therefore future results.
The basic model that implements the linear regression method is to look for the straight line with the smallest deviation from the actual measurements (both positive and negative). However, this is a way for the described points that brings a great simplification, because it is difficult to approximate the results of actual measurements on a graph, with sufficient accuracy, with a straight line.
In energy consumption control systems, the linear regression method is useful for selecting values that are linearly independent but affect key parameters of power consumption (usually converted per unit of output). In this way, it is possible to narrow down the set of variables important to monitor, such as temperature or pressure, for example, which affect the energy usage of the selected consumer.
Energy-efficient operational management must be carried out for each relevant component of the receiver system. Such operational management can, for example, be anchored in a work instruction or functional description. This operational management must be coordinated with the responsible shift or plant managers.
People who do their work on the shop floor are usually also a factor in reducing energy consumption. Therefore, they should be made aware of their tasks in order to keep energy consumption as well waste energy costs as low as possible. Specific tasks and solutions for them should be described (e.g., if a predetermined limit is exceeded, measure X should be applied).
There are three key elements in any project: process, people, and technology. While all of these are important, the most important, and most challenging, factor is people. It is important to motivate them, help them understand the meaning of change, and know how to implement new processes. Even the best solution will not produce positive results if the user interface is inappropriate. For the sake of improving 5he efficiency of energy usage, as well as for many other benefits, it is always a good idea to put people, including everyone involved in an issue, at the center of a project.
Any opportunity for improvement must be visible and documented. Regression analysis can be used to prioritize specific projects by forecast and predicting potential savings. If all of this is put into the context of the necessary investments and schedule, then priorities can be set very quickly.
Ideally, these improvements can also be entered into the CIP database. If the improvement proposal is approved, it will be included in the designated catalog of measures for this important consumer. It is important that these decisions are made transparently and that the originator receives appropriate feedback.
Plant changes must be explained to operators in a way they can understand. Therefore, previously developed steps should be recorded in a training plan that serves as training for the relevant people in the area.
Energy savings and planned operations must be translated into projects. The production department focuses on projects, not energy savings. Therefore, it is important to transfer projects to a project management tool and track and organize activities there. At the same time, the actual energy savings from individual projects must be visible to the energy manager. So integrating the project management tool with data analysis is key.
You can use regression analysis to find specific, detailed, and effective solutions for energy-saving projects. An integrated project management tool is the best way to plan and track activities and determine actual energy savings achieved at the “push of a button”. With these tools, you are prepared for the future.
There can be many reasons to focus on energy savings:
Regardless of which one you prefer, the key is to have a good approach and choose the right initiatives, the best areas, and tools in terms of energy consumption. Performing energy audits, using energy-saving tips, and introducing new technological solutions can make a significant contribution to improving your consumption efficiency and reducing energy costs.
An automotive company needed a solution to monitor production to improve the quality of final products. The key element was identifying issues by analyzing quality data correlated with production data. Special attention was given to the casting and cooling zones, where product quality was particularly variable.
A global company in the electrical accessories manufacturing industry used in automation faced the challenge of improving key performance indicators (KPIs), particularly increasing the availability and efficiency of production cells. Each workstation involved multiple stages of assembly and production across various positions and locations, requiring a coordinated approach to managing work, materials, and proper planning.
A client, a leader in the glass packaging manufacturing sector, identified the need to implement an integrated production data management system to replace outdated, manual reporting methods.
Introduction In the highly competitive food and beverage industry, achieving optimal Key Performance Indicators (KPIs) such as availability, performance, and quality is essential for maximizing operational efficiency and profitability. A client operating semi-automated production lines was experiencing persistent underperformance in these KPIs. To address this issue, the company required a robust and precise data-driven approach […]
In the aerospace and defense industry, which is characterized by particularly high requirements for precision and reliability, key performance indicators in maintenance, failure prediction or machine condition monitoring, are crucial.
Industry 4.0, also referred to as the fourth industrial revolution, is a concept encompassing a complex process of technological and organizational transformation of companies, which began in 2013.
If you think OEE has no secrets to you and your plant maintain highest OEE results… think again. Harsh truth is that most manufacturing plants’ OEE land somewhere between 35 and 43%. They just don’t know about that.
You don't have to replace your machines with the new ones to make your production "smarter" and more efficient. Your shop floor is a data mine, and digitization is the key to unlock its value.
Whether you're a seasoned user or new to ThingWorx, overcoming these hurdles is crucial for IoT success. In this blog, we'll uncover the top challenges, offer tips for newcomers, discuss strategies to enhance your ThingWorx experience, and explore the importance of upgrading your ThingWorx solution.
Very often overlooked or accepted as-is due to being an integral part of the production – in times of crisis and cost-cutting, it can become a major factor that improves the bottom line of your organization. Where to look for significant energy savings to reduce energy costs? How manufacturers should focus on these goals to make an impact?
In the manufacturing industry, efficiency is key to staying competitive and profitable. One way to improve efficiency is through data visibility. By having access to real-time visibility of the operational data throughout the manufacturing process, companies can identify bottlenecks, monitor production lines, and make data-driven decisions. In this article, we'll explore how data visibility can help manufacturing companies improve their efficiency and ultimately their bottom line.
Energy consumption bills have been a major focus in virtually all areas of industry for many years, and the current global situation is a factor driving up demand for solutions that make it easier to monitor energy consumption or save energy. In an industrial environment, where the cost of utilities has always been one of the main business drivers, the latest twists and turns in the global economy: inflation, natural resources supply challenges and the threat of fluctuating and unpredictable increases in energy costs – are arguably the most important economic factors these days.
The new opportunities associated with Industry 4.0 require companies to adapt to the new environment. In this article, we take a closer look at the current situation in the automotive industry, discuss the challenges it faces and the opportunities offered by digital transformation.
Digital transformation is reshaping the way how people, products, assets, data, and operations are connected to create an outcome for the customers and switch digital data into the customer experience. Digital technologies create new business opportunities across the globe and enable the evolution of enterprise, products and processes for valuable capabilities. The article describes the Internet of Things concept and shows how to use cloud infrastructure to take advantage of the digital transformation in business.
Internet of Things systems have one huge advantage – they can collect lots of data. Temperature, items produced, amount of remaining liquids, humidity, machine uptime, damaged products, vehicle routes, electricity used. Based on this, we can get even more value by calculating KPIs to indicate how close to perfect our system is. Going manually through an endless stream of numbers changing every couple of hours is impossible and inefficient. The simple solution is to visualize the data by using a carefully selected chart type, that will exponentially increase its value. In this article, I want to show you the benefits of good data visualization and explain how it can be applied in your solution.
The sudden epidemic of SARS-CoV-2 coronavirus and the COVID-19 disease has affected every sphere of the modern world. Caused by an epidemiological threat, the restriction of the flow of people, goods and services has already negatively affected the continuity of production processes in many industries, and each day this situation persists, without credible forecasts of a return to normality, will pull others into the spiral of detention threats.
Scalability in web applications has become crucial in the past years. An ever-growing number of devices and clients, connected to the Internet, makes it difficult to handle the traffic by a single server. Scalability is a characteristic of a system that tells if expanding the resources of a server(s) will make it run faster (or handle more load).
Modern web applications that serve data and content to millions of users run in clustered environments. Dealing with a huge amount of connections at the same time requires many resources. That resources are CPU time and RAM. Each and every connection produces an additional load on the server. Having just one server would require a vast amount of resources and we already know that Moore's Law is no longer valid. That said we need multiple servers ready to respond to users’ requests. Web applications use HTTP(S) protocol which works in the request-response communication method. Upon user's request, the server will prepare the response and send it back. Every response needs to be processed by the server and that's the key factor in provisioning resources for the server - requests may be different, starting from simple static data like CSS or images to more demanding like requesting data from database, filtering or calculating certain data.
The ThingWorx IoT Hub Connector is the bridge that connects the ThingWorx platform to the Azure cloud (more specifically to Azure IoT Hub). It provides secure (certificate-based) communication, thanks to which we can use the enormous possibilities of cloud computing. It is also a very extensive, but generic solution.
Synergy, this is how you can define this natural combination of technologies that will significantly affect the appearance of the future of production. Recently, in addition to the Internet of Things (IoT), artificial intelligence (AI) is gaining more and more popularity. The connection of these two technological trends heralds a real revolution in industry 4.0.
This year's Liveworx, due to the global situation caused by the COVID-19 pandemic, has exceptionally been held only online. On the very first day it was announced that a new version of ThingWorx - the most popular platform maximizing the potential of the industrial Internet of Things - will be released for commercial use. According to the announcements of Joe Biron, CTO responsible for IoT technology at PTC, it is supposed to be faster, cheaper and more effective.
The evolution of artificial intelligence, as well as machine learning has gained momentum in the last few years. The constant drive to increase the computing power of computers has given the opportunity to use algorithms and mathematical apparatus created in the second half of the 20th century on an unprecedented scale. With the imminent arrival of a commercial quantum computer, we can slowly become afraid of scenes from the movies with Arnold Schwarzenegger as Terminator. However, without going too far into the future, and focusing on the present, I decided to check the possibilities offered by the technology available today and whether it can be used to predict the spread of COVID-19 disease.
The Industrial Internet of Things changes our view on the classic concept of production today. The largest manufacturing companies are eager to reach for technological solutions that streamline and increase the efficiency of production processes. With the development of subsequent technologies, interest in the concept of industry 4.0 increases, and thus, the number of connected devices. To meet the demand for infrastructure with adequate capacity and speed it was necessary to evolve towards the next generation of networks - 5G. How will 5G affect the development of Factories of the future and why is this crucial from the perspective of the Internet of Things? You will learn everything from the article.
The Internet of Things is being used more and more, and even global giants are already using the optimization or information gathering solutions. All this to improve existing processes, acquire, process and report more data, or even introduce new services for their clients, thereby increasing sales revenue. How is the Internet of Things changing the reality of the aviation industry?
Following up our partnership with Rockwell Automation, our team of business and technical experts found their way to Munich, Germany to participate in TechED EMEA. It is a unique event during which you can listen, talk and test the latest news in the field of industrial automation and directly participate in the next industrial revolution.
Nobody would be surprised by a statement that the Automotive industry is innovative in its nature. Cars are machines that historically revolutionized many areas of industry themselves, and today we can’t help but notice that the industry has not slowed down even for a moment and has always been focused on technological growth that serves both the business and its customers.
It might seem that the Internet of Things is dedicated only to industry. However, transport and logistics are closely connected to it, and they can also take advantage of the ongoing revolution. In the end, every industry uses transport services or logistic processes to some extent.
As every time for the last couple of years, our strong team of representatives was present in Boston to attend one of the most important IoT events of the year – LiveWorx, 2019 edition. Get the ball rollin’ And even with 10 participants from various business areas, actively seeking new information and presentations, […]
Industry 4.0 and its foundation, the Internet of Things (IoT – especially in industrial version: IIoT), in the last years have dominated the way of thinking of advanced management concerning manufacturing business resources.
PTC is phasing out its Axeda platform. Although they look similar at first sight, Axeda and ThingWorx differ very much in capabilities.
While ago, PTC announced a new release of ThingWorx Platform (8.4). Among other exciting features, this release has OOTB support for integration with InfluxDB.
The approach that has been underestimated for a long time is nowadays spreading its wings and becoming a crucial set of solutions for global corporations. However, not only for them as medium and small companies are following the biggest ones as well. Thus, the advantages of the Internet of Things have been recognized by everyone. […]
Recent years were hyped about the Internet of Things (IoT) and how it was supposed to re-shape the whole industry. However, so far we’ve seen many more people talking about it than actually implementing it enterprise-wide. Is IoT mature enough to be “the real deal” and bring measurable value to businesses? The term IoT […]
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