Automation indistory

Artificial intelligence | SMEs need help with technical implementation

Artificial intelligence is still little used in production – especially in medium-sized companies. These challenges still exist in companies.

Artificial intelligence
Artificial intelligence

In industrial companies, the expectations of artificial intelligence (AI) are high, but it is still not used much in production – especially in medium-sized companies. There is ambiguity, for example, in the assessment of the economic benefit, the applicability in one’s own production environment as well as in the collection and use of data. This is the result of an online survey conducted by the AI ​​innovation project IIP-Ecosphere with the support of the project partner VDW.
The Federal Ministry of Economics is funding IIP-Ecosphere as part of the AI ​​innovation competition to accelerate the use of AI in production. The aim of the survey was to determine the current status and practical challenges of companies with regard to the use of AI and related topics such as data collection, cloud use, selection and framework conditions of AI solutions and Industry 4.0 platforms. “With the survey, we wanted to show necessary, real fields of action in which IIP-Ecosphere can now actively act as an accelerator for the utilization of AI methods,” explains Dr. Claudia Niederée from the L3S research center, project leader of IIP-Ecosphere. 75 companies took part in the survey, two thirds of them from the machine tool industry.
The podcast episode with AI expert Markus Ahorner is also about artificial intelligence:

More than half have not yet had time to deal with AI

What is striking is the high participation of larger and very large companies, at 70 percent. The background could be a greater preoccupation with AI topics compared to medium-sized companies. Compared to other surveys, a relatively high proportion of over 37 percent of those surveyed stated that they were already involved in AI-based solutions in their company. In contrast, however, there are more than half of those surveyed who find the topic of AI exciting but have not yet had the time or opportunity to deal with it.
Overall, the answers show high expectations of AI and its benefits for products and services. 60Percent of the respondents express themselves accordingly. Only 7 percent state that AI is overrated. Most of those surveyed agreed that AI should be used to support and not replace people in production.

Assessment of practical use difficult

The number of providers and solutions for the implementation of AI projects in production is growing steadily; the market is becoming increasingly confusing for users. What makes the selection even more difficult: Often several AI solutions have to be integrated into hardware components, such as machine controls. This complexity is reflected in the classification of solutions: the most common obstacle in identifying suitable AI solutions, at 65 percent, was problems in evaluating the economic benefit of an AI solution for their own application context.
At 64 percent, in second place is the question of whether the respective AI solution can be used at all in its own context. “In order to offer companies a faster overview of available AI solutions and their applications, IIP-Ecosphere is developing an AI solution catalogue, which addresses the problems of those surveyed and includes aspects of benefit and applicability,”

Legal uncertainty on the subject of data sharing

The survey results show that over 90 percent of companies already collect production data. However, almost half of those surveyed say that collecting the data needed for AI solutions poses problems for their company. There is therefore a clear need to catch up when it comes to the needs-based collection of AI-relevant data.
A mixed picture emerges when it comes to data sharing: On the one hand, 57 percent of those surveyed think that the Other companies’ data could benefit, but only 16 percent would purchase non-company data. 59 percent still see a need for clarification on the legal issues. “The responses of those surveyed also make it clear how necessary it is to understand the legal regulations in order to be able to clarify the framework conditions for the use of external data,” says Hans-Dieter Schmees, project manager for technology and standardization at the VDW.
Almost half of those surveyed stated that they use cloud solutions to handle internal company data. Interestingly, however, around two thirds of the companies also agree that production data must not leave the company. Just under 10 percent of those surveyed who commented on cloud solutions primarily rely on an on-site solution and would not use a cloud solution.

IIoT platform mainly used by larger companies

Industrial production is increasingly using IIoT platforms that support the coordinated control of machines and the centralized collection of data. Almost a third of the companies surveyed are already using such a software solution, and almost 45 percent have not planned to use it. Almost 7 percent of the companies that use a platform use their own development. According to survey results, however, it is primarily larger companies that are already actively using IIoT platforms. dr However, Holger Eichelberger from the Software Systems Engineering working group at the University of Hildesheim estimates a trend towards the increased use of IIoT platforms, which is also confirmed by the survey: “In the medium term it can be expected that around half of those surveyed Companies from large corporations to SMEs will soon be using such software.”
An obstacle to the use of AI, which was mentioned in particular in the free comments, is the age of the company’s own production machines, with which the necessary data cannot be recorded or can only be recorded with great effort. Concerns are therefore arising, especially among SMEs, that they could miss out on Industry 4.0 and AI. In addition, some companies are afraid that research and business development will lose sight of them or that they have no opportunities to (help) shape relevant developments. “Cooperation in a spirit of partnership across disciplines is therefore essential for future clout and for securing a competitive advantage, at least in the classic, economically strong disciplines,” says Dr. Alexander Broos, head of research and technology at the VDW.
The open ecosystem approach of IIP-Ecosphere with many participation opportunities and offers offers companies the chances and opportunities they need to tackle challenges together and to develop technological alternatives that make AI accessible to as many companies as possible.

Biomass Energy | Benefits and Typical Applications of Biomass

 Biomass Energy
Biomass Energy

Biomass in the form of firewood was perhaps the first source of energy used by humans and was the main burner until the Industrial Revolution, after which fossil fuels like coal and oil replaced biomass as the main fuel. Biomass is still an important fuel in developing countries. According to the International Energy Agency, energy from biomass accounted for 11% of the world’s final energy consumption in 2001 (Karekezi, Lata and Coelho 2004). In Latin America, this proportion was 18%, in Asia 25% and in Africa 49%.
Biomass energy offers several benefits in terms of energy security, socio-economic development and the environment.

Energy security

Decentralized energy from biomass could help to significantly reduce dependence on fossil fuels.

Rural economic growth

Biomass energy could promote growth in agriculture, forestry and rural industries leading to general rural development. In addition to plantations, biomass energy could also offer a productive way of using agricultural and forestry waste.

Environmental Protection

By balancing the use of fossil fuels and related emissions of nitrogen oxides, sulfur dioxide and other pollutants, the energy from biomass will contribute to clean air and water. In addition, increasing the number of carbon fusing plants will help reduce the greenhouse gas emissions that contribute worldwide.
It is estimated that around 2.4 billion people worldwide rely primarily on biomass fuels to provide energy for cooking. In addition to cooking, biomass fuels are also used for process heating, steam generation, mechanical and shaft power, transport fuels and power generation.

Examples of biomass commonly used as fuel include:

⦁ Firewood,
⦁ agricultural residues such as husks and stalks,
⦁ Vegetable oils and
⦁ animal waste.

In recent years the world has seen tremendous interest in biofuels and a great deal of research has been directed towards finding new biomass resources and processes for producing biofuels.
A variety of physical, thermochemical, chemical and biochemical processes are used to convert biomass into energy. In this chapter, we will examine three modern biomass energy technologies (see Table 1.1) that can be applied in a decentralized manner and that have proven useful in the context of developing countries.

Table 1.1. Decentralized modern biomass energy technologies

A variety of physical, thermochemical, chemical and biochemical processes are used to convert biomass into energy. In this chapter, we will examine three modern biomass energy technologies (see Table 1.1) that can be applied in a decentralized manner and that have proven useful in the context of developing countries.


Table 1.1. Decentralized modern biomass energy technologies

technologyType of biomassConversion processTerminate applicationsTechnology status
Wood, woody
biomass, agro and
process which
converts biomass
into producer gas
Power generation:
10 kW -1000 kWe.
Thermal applications in
small industries up to 3
Dual fuel and
100% gas
engine based
BiogasAnimal faecesBio-methanation
process which
converts biomass
into biogas
Household Cooking,
Driving, and
Power Generation
often have to be
vegetable oil
Extraction of bio-oil
from the oil seeds.
production through
Driving force and
power generation
Biodiesel and
Oil (SVO)
as shown
fuels for
and power

In general, the conversion efficiencies are very high compared to the traditional technologies for biomass energy production (e.g. traditional wood-burning stoves) it is common that these processes also produce a large number of nutrients for sustainable agriculture, e.g. Liquid manure from biogas plants, oilseed cake made from vegetable oil seeds (Karekezi, Lata and Coelho 2004).

Successful project

One of the first successful applications of a biomass gasifier for rural electrification in off-grid mode is the 500 kW gasifier plant on the Gosaba island of Sundarban in India.
The plant was built in 1997 and consists of 5 x100 kWe units. The gasifiers are closed extraction systems based on wood biomass. The system has dual-fuel engines. The transmission and distribution line extends over a length of 6.25 km of high-voltage line and 13.67 km of low-voltage line. The plant supplies around 900 consumers. The facility is managed by a local cooperative and the state government.

Typical uses of biomass

During the Second World War, carburettors were mainly used for transportation purposes. In recent years, however, carburettors have mainly been used for stationary applications.

A. Electricity generation

To generate electricity, the gas from the biomass gasifier is first cleaned and cooled and then used as fuel in an internal combustion engine. A generator coupled to the engine generates electricity.
Biomass gasoline engine sets are typically available in outputs from 10 kW to 500 kW. Two types of motors are used. Diesel engines are modified and can be operated with a mixture of diesel and production gas. These are known as dual-fuel engines. As a rule, 60 to 85% diesel is replaced by generator gas. 100% producer gas engines are now also available – as the name suggests, these can be operated with 100% producer gas.
Electricity generation based on biomass gasifiers was typically used for three types of applications:

A.1 Village electrification in off-grid mode

In recent years biomass gasifiers have been used to electrify remote villages. The size of such systems can vary from 10 kW to 500 kW. In India, several of the smaller biomass gasification systems (10-20 kWe) were built under two government proposals called the Remote Village Electrification (RVE) and the Village Energy Security Program (VESP). In addition to the government programs, several NGOs and companies have set up such systems.
There have been some cases on Gosaba Island in Sundarbans, India, such as a 500 kW biomass gasifier based power plant using large capacity gasifiers.

Gosaba rural electrification project

One of the first successful applications of the biomass gasifier for rural electrification in off-grid operation is a 500 kWe gasifier system on the Gosaba island of Sundarban in India. The plant was built in 1997 and consists of 5 x 100 kW units. The gasifiers are closed extraction systems based on wood biomass. The system has dual-fuel engines.
The transmission and distribution line is distributed over a length of 6.25 km of high-voltage line and 13.67 km of low-voltage line. The plant supplies around 900 consumers. The facility is managed by a local cooperative and the state government.

A.2 Grid-connected biomass gasification power plants

There are a few examples of on-grid biomass gasification power plants. These are relatively large carburettors with outputs in the range of several hundred kilowatts. A typical example is shown below

Arashi Hi-Tech BioPower Pvt Ltd, Sulthanpet, Coimbatore, Tamil Nadu

Arashi Hitech Bio makes an independent power The manufacturer (IPP) has built a gas-fired power plant that is connected to the state grid. It is located in the village of Sultanpet in the Coimbatore district of Tamilnadu, where coconut shells are abundant. The power plant comprises a biomass processing system, a gasification system, a PLC-based automation and control system, a full-fledged water treatment system, a power pack and an energy drainage system. In the first phase, in July 2002, an 800 kg / h gasification system with a marine diesel engine with low speed was integrated.
The power plant was operated in two-fuel operation with an average load of 600 kW for almost 6000 hours. The average liquid fossil substitute is 68%, the specific biomass consumption is between 0.6 and 0.7 kg / kWh. Recently the dual-fuel engine was replaced by 5 x 250 kW gas engines.

A.3 Biomass gasifier for self-generation of electricity

Biomass gasification plants in an industry or an institute are usually used as a captive power generation unit. 

B. Thermal applications

A very large number of micro, small and medium-sized enterprises (MSMEs) use biomass and fissile fuels to generate heat. Given the continued rise in the price of fossil fuels and their scarcity (quota) in the free market, many of these small businesses face serious problems in controlling the cost of fuel and thus maintaining competitive prices to exist in the market.
The gasification technology offers them an option to have all the advantages of gaseous fuels with comparatively cheaper, locally available solid biomass fuels. There are various fuel-fired stoves that are ideal for converting to biomass generator gas. The work is listed in

ArtApplication / temperature (° C)
Forge furnace1200 -1250
Temper rolling mills900-1200
Directly fired process heatingFood, textiles, paper, printing, chemicals, rubber, plywood and
plastics industries
dryerPaper, cardboard, wood and timber, textiles, ceramics,
tobacco, plastics, paint, food and pharmaceutical industries
OvensPlaster of Paris, glass-ceramic plumbers, brick, and
structural clay and concrete industries.
OvensLow temperature (between 20 and 370 degrees
Celsius) cooking, baking, curing or vulcanizing (a
treatment that stabilizes and gives elasticity) rubber or
plastic. The food industry uses ovens to make bread, biscuit
crackers, pretzels, while the rubber and plastics industries use
the lower temperature found in ovens in
production of tires, shoes, hosiery and rubber bands (e.g.
fan belts).
Small boilerDifferent industries
Table 4

There is now a great deal of experience in the use of thermal gasifiers for industrial applications. Good documentation of the various applications can be found in CII (2005).

Industry 4.0

Industry 4.0
Industry 4.0

Industry 4.0 is the digital transformation and automation of traditional production companies. Industry 4.0 is often referred to as the “fourth industrial revolution” or “smart manufacturing”. By digitizing machines and systems, including the Internet of Things (IoT), traditional processes and procedures should be made more intelligent and autonomous. Industry 4.0 affects a whole range of sectors such as construction, food and beverage, aerospace and the automotive industry.
Industry 4.0 increases productivity, lowers costs and improves international competitiveness. Read on to find out more about Industry 4.0. Learn more about the new technologies that are transforming traditional manufacturing operations into smart factories and get an idea of ​​the advantages and challenges facing production areas.

What is Industry 4.0?

Under Industry 4.0 means the optimization of traditional manufacturing industries through the Internet of Things (IoT) and other technologies. In addition to automating production, these new technological possibilities enable complete digital transformation. The aim is an optimized and data-driven production environment.
The driving factor of Industry 4.0 is data obtained through networking. Technologies from the field of Industry 4.0 record and collect data from production independently of company or machine systems. IoT, cloud computing, data lakes and other computer-based technologies are used. These technologies can improve traditional manufacturing industries through data-driven process optimization. Manufacturing facilities are becoming more efficient and flexible and can produce high-quality products at lower costs.

Industry 4.0 is the next after the three well-known and successful industrial revolutions. The first industrial revolution (around 1760) came about as a result of the invention of the steam engine and enabled the transition from manual to machine production. The second revolution (around 1870) is also known as the technological revolution and included numerous technical improvements such as electricity and railways. The third revolution (the 1960s) brought computerization and was characterized by the use of computer systems for mass production and automation. We are now experiencing the fourth revolution, which is driven by data and the IoT.

The term Industry 4.0 has existed since 2011 and came up as an idea and strategic initiative of the German federal government and German industry. The German economy is heavily dependent on traditional sectors such as mechanical engineering or the electrical, automotive and pharmaceutical industries. In order to remain internationally competitive, Industry 4.0 technologies are increasingly being used in German factories. 
The digitization of the manufacturing industry is also being promoted. In Germany Industry 4.0 is also associated with the term “Work 4.0”, a conceptual framework for the discussion about the future of work.
Let’s take a look at the technologies Industry 4.0 offers for smart production lines:

12 Industry 4.0 technologies

Industry 4.0 knows twelve essential industrial technologies and trends.

Additive manufacturing

3D printing and digital manufacturing to create lighter, better performing parts and systems. Additive manufacturing enables quick and individualized implementation. Manufacturing companies can manufacture the parts they need themselves, precisely when and in the required design.

Advanced Robotics

Modern autonomous robots will work side by side with humans. Robots enable new forms of collaboration, higher speed and higher efficiency. They also reduce costs and improve workplace safety.

Augmented Reality

Augmented Reality technologies can be used to control robots, for maintenance, assembly and repair work, for training purposes and quality controls or for monitoring production processes and for auditing systems. With augmented reality, companies can reduce errors, improve security, save time and cut costs.

Big data and data analysis

This means the acquisition and analysis of data from various sources, e.g. data from conventional machines and sensors or from customer relationship management software (CRM) or enterprise resource planning systems (ERP). In most cases, Industry 4.0 solutions enable manufacturing companies to systematically collect data from parts of the supply chain for the first time. With big data analyzes, managers can make data-based decisions, which leads to optimization and increased productivity.


The implementation of cloud computing technologies enables the storage, management and sharing of data. For the growing amount of data generated by smart factories, the cloud is essential. It enables scalability and improves collaboration.

Cyber security

Cyber security ensures secure communication between machines, devices and industrial systems, especially in systems that are being networked for the first time. A high level of cyber security is essential to maintain confidentiality and data protection. Cyber security prevents data breaches that could endanger the entire plant.

Horizontal and vertical system integration

This is about the complete integration of all data from all departments, teams, functions, production and components and that across the entire value chain. Complete integration is essential for end-to-end monitoring and for building a reliable database (SSOT-Single Source of Truth). This database serves as the basis for decision-making, the allocation of resources and the organization of cooperation in order to enable lean manufacturing. This is also one of the greatest challenges of Industry 4.0.

Simulation / digital twin

A digital twin is a virtual copy of a real process with real data. Before a decision is made, simulation tools are used to test and optimize processes. In this way, error rates can be reduced, costs lowered and processes optimized.


Sensors connected to machines enable performance, system and environmental characteristics to be recorded. Manufacturing companies can use sensors to collect data from production. This data can be used for monitoring purposes, for predictive maintenance, to optimize processes and improve machine availability, or in general for data analysis.

AI (Artificial Intelligence)

AI enables the optimization of tools, technologies and processes through intelligent machine algorithms. In principle, AI technologies can always be used to improve Industry 4.0 solutions, for example, to improve monitoring, maintenance, robotics or operational management.

11. ML (machine learning)

With machine learning, a branch of AI, manufacturing processes can be optimized on the basis of recorded and collected data. This also includes calculation models and algorithms from the field of operational excellence.

12. Industrial Internet of Things (IIoT)

This means the digitization of all devices and machines used in industry. Older machines without their own control can also be digitized. The IIoT enables collaboration, data acquisition and optimization in real-time. The industrial Internet of Things forms the basis for generating data for most other Industry 4.0 technologies.

Advantages of Industry 4.0 for manufacturing companies

Industry 4.0 is useful in many ways for manufacturers in a wide variety of industries, from food production to automotive suppliers. The following benefits are mentioned as examples:

Productivity and efficiency

The main benefit of Industry 4.0 and smart factories is that the respective industries can increase their productivity and improve their efficiency. How does it work? With Industry 4.0 technologies, production companies can collect data and use the analysis of this data to improve their key business figures. The new processes ensure data-based and therefore more intelligent decision-making. Bottlenecks can be identified and resource allocation optimized. Barriers are removed and, as a result, machine availability is increased, so that performance and production quality increase.

Cost reductions

As a result of improved productivity and efficiency, costs decrease and profits increase. The costs also decrease thanks to improved resource allocation, shorter production times and fewer downtimes, thanks to improved quality and less waste or rejection. In addition, so-called predictive and preventive maintenance enable optimized machine maintenance. Wear and tear are reduced and depreciation is increased. Although Industry 4.0 naturally requires a certain initial investment in new technologies, the return on investment (ROI) is still significant.

Traceability and transparency

The networking of all machines and systems enables data to be collected. This information can be used to transparently track the performance and output of the machines. This enables managers to better monitor and control operational processes. This enables the optimization of production processes and the improvement of product quality. Key figures can be set and monitored. In addition, the data can also be used to comply with legal regulations more easily.

Agility & Innovation

Industry 4.0 enables deeper insights into production. You will then better understand where the bottlenecks are, introduce scalable technologies and work together better on processes. Production companies are thus given the flexibility and agility they need to reorganize the allocation of their resources, introduce new processes and implement ideas.


Many manufacturers are still competitive due to lower costs and increasing product quality, even without cuts in wages or even outsourcing to low-wage countries.

Industry 4.0 challenges

Even if Industry 4.0 brings many advantages, there are also some challenges

Initial investments

Industry 4.0 offers a very advantageous return on investment (ROI), but also requires a certain investment that not all companies may be able to shoulder. This includes, for example, investments in new technologies, training courses and machines. Adjusting business models can also result in costs.

Data protection and security risks

When communicating between devices (D2D – Device to Device) and machines (M2M – Machine to Machine), personal data can also be exchanged. Data breaches in the company’s own production facility or at third-party providers could make this data accessible to attackers and endanger data protection with regard to PII (Personal Identifiable Information). Furthermore, there are fundamentally new attack surfaces and weak points from networking via IoT. These two topics require appropriate government regulations and also new cybersecurity technologies.

Training of the workforce

Operating a conventional machine requires different skills than operating a conventional machine connected to a computer. Managing traditional industrial production is different from managing data-driven, automated production. Industry 4.0 brings new technologies and functions that require a change in the mindset of employees and other skills. For this reason, companies have to train their employees and also ensure a new corporate culture. This takes time, effort and resources.

Dependence on technology

Industry 4.0 technologies can “free” older processes, but companies are still restricted by existing technologies and their operating personnel. For example, networked devices and machines require IT teams in the factories. Companies have to analyze large amounts of data and are therefore dependent on AI algorithms and computer scientists. While Industry 4.0 is gradually gaining ground, many of these technologies are still in development. Therefore, not all challenges of today’s modern factory can be answered by Industry 4.0.


The connection of different systems and machines to a common business process requires standardization and technologies that are not always available.

An entry into Industry 4.0

Switching to Industry 4.0 is not always easy. In the beginning, an initial investment is always required and you have to find the right technological solutions for yourself. Employees have to be trained and given confidence in the process of collecting and evaluating data.
A simple way to get started with Industry 4.0 is to implement a universal, non-invasive technology.
3d Signals offers an IoT solution that can be set up easily and non-invasively on your machines (without interfering with the machines). You can use it to collect data and gain usable insights immediately. Increase the availability and productivity of your machines right from the start. View data from your machines in real-time, optimize your production processes and increase productivity.

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