Your browser is not supported. Please use Chrome, Firefox, Edge or Safari browser. More information

SolutionsSector digitalization4iOP Industrial Digitalization Platform


Digital upgrade with the 4iOP product family

Industry 4.0 mainly integrates data from separate expert systems and analyses them together to take production to a higher level.

The continued development is being accelerated by ever-expanding next-generation technologies, such as intelligent robots, drones, sensors, and 3D printing. In addition to the increasing availability of new technologies for production companies, customers and clients are also increasingly demanding in the analysis of production process data.

Industry 4.0 is an area that relies on IT solutions by orders of magnitude more than in previous practice; its problem today is no longer the applications companies use, but how to find integration opportunities with the help and guidance of system integration IT companies, to make the highest possible use of information and data from systems serving core activities (ERP, CMMS, MES, WMS, etc.). Therefore, system integrators need to adapt to the changed needs of the field, they need to prepare for the implementation of IT systems serving the core activities of the industrial field (e.g. production of digital twins, integration tasks, activity – automation systems, machine learning supported analysis – intervention, IT security systems).

As a system integrator, 4iG also relies on a significant expert knowledge base and a number of its complex projects successfully implemented. 4iG is actively involved in the development of customized solutions at manufacturing and production companies. These can achieve significant increase in efficiency, giving our customers a great advantage in competition.

The demand for industrial digitalization developments is growing in almost all areas: in the automotive, electronics, pharmaceuticals, FMCG and oil industries. As there are significant benefits to digital transformation regardless of industry, it is easy to discover similarities with Lean strategies and tools in this area. It can be said that companies that have standardized their business and manufacturing processes in a timely manner can now switch to Industry 4.0. In order for a manufacturing company to rise to a higher technological maturity level, it is generally a prerequisite that industry 3.0 technologies and expert systems are already in use at them extensively. From here, they can achieve the next step in their development: to data-driven automation and robotization – to industrial digitalization itself. This development is driven by a variety of engines in the world, such as:

  • the rapidly changing market and customer needs,
  • the advancement of competitors in quality and developments,
  • the limitedness of human resources,
  • ethe growing expectations in the supply chain and ecosystem, but the goal is always uniform, industry 4.0 solutions must have a growth impact: in efficiency, in quality, in logistics and in profit.

WHY 4iG?

4iG offers effective solutions to the following manufacturing problems:

  • in identifying real bottlenecks, in predicting machine downtimes and unplanned failures, in making intra-logistical losses visible, in objectively measuring downtimes and identifying the causes,
  • when there are frequent changes in customer needs, expectations and in technical content,
  • when process monitoring is incomplete, when the objective performance measurement is incomplete, when there is a lack of decision support tools, and the rapid and regulated escalation of events is cumbersome,
  • in queuing, congestion problems, when there is a lack of optimal storage locations and routes, and a lack of capacity analysis and planning,
  • when the automation of quality control and the possibility of immediate intervention and action are not implemented,
  • when the performance tracking of workers and operators is not resolved.

We have proven in many industries that our approach beyond IT systems helps our clients to achieve their business goals significantly. In addition to the systems (products) that can be implemented immediately, our approach extends to a long-term partnership based on joint innovation. However, a successful business digital transformation cannot be established without stable IT foundations, including technology, processes and human resources and expertise as well. 4iG's complex digitalization approach helps to prepare the organizations of its customers more efficiently for the new operating models required by the digitalized economy.

4iG Industry 4.0 solutions combine production, manufacturing, technology and logistics processes to digitalize business processes, thereby contributing to the efficient operation of the company.

An important step towards Industry 4.0 is the ability of individual expert systems to communicate with each other and to make appropriate use of the benefits of such ability. Integration is needed for this task to be carried out without a new installation or deployment using existing expert systems. Integration always means a specific software development, in which data exchange is carried out between the source and the target system, whether it is the connection between a security system motion sensor and the heating automation system, or even between the HR register and machine start-up authorization.

4iG is an industrial IT system integrator:

  • where 100% of internal industry expertise (domain knowledge) has developed the functionality of expert systems in line with market expectations,
  • where preparation for data communication between expert systems is the basic requirement in the design and development of the product,
  • who helps manufacturing and production companies develop unique solutions that can help them achieve significant efficiency gains, giving our customers a significant competitive advantage in their own sectors.


4iOP ( is an industrial digitalization platform and framework developed by 4iG, that can generally offer solutions at all levels of production which are tailored to specific production processes rather than ‘boxed’ solutions. This digitalization platform can also be built modularly, so it is not necessary to buy the entire end-to-end system, as it is scalable in itself. 4iOP products act as a kind of layer on the platform where any element can be added separately. 

4iG's 4iOP manufacturing cell optimization (MCO), energy management and camera sensor systems help you economically increase your production efficiency and quality. Machine learning solutions should be used primarily in companies where traditional analytics systems have failed. This could be a production line that has been touched so many times that another solution, such as a contactless solution, was needed. In order for a company to build on old models to make further significant progress, it is necessary to use a more advanced system. 

Currently, the 4iG team of experts is working with the following Industry 4.0 solutions:


Predictive analysis systems are the combination of predictive analytics statistics and modelling techniques to determine future performance. These systems are used as decision-making tools in many industries and scientific disciplines, such as insurance and marketing. 

Predictive analytics are used to respond to customer answers, or to determine their purchases, or to promote cross-selling opportunities. Predictive models help businesses to attract, to keep and to increase the number of the most profitable customers. Our experts use predictive models to forecast inventory and to manage resources. 

Predictive analytical module is able to change the maintenance of production machines and equipment from reactive and preventive maintenance to state-specific maintenance using information from machines, PLCs, controllers and various sensors to predict failures, thereby reaching higher machine mileage and reducing unplanned downtime.


Visual analytics systems use analyses and arguments on information sets using some visual tool. They combine the best of man's abilities (decision-making, analysis and reasoning) with the computer's number scrolling skills through a visual interface. 

Visual analytics integrates new computing and theory-based tools with innovative interactive techniques and visual representations to enable human information discourse. The design of tools and techniques is based on cognitive, planning and perception principles. 

The visual analytics module is capable of processing the identification of quality defects in products (surface damage, defects in shape, mechanical deviations, etc.) in a short period of time (msec), which can also be used for quantitative counting of products in production companies with shorter cycle times and high quality score.


This system can answer questions about what kind of things are there and where they actually are. In fact, it's a sensor that can be placed anywhere, which can be a device or even a human resource. This way we can control the needs that arise and their tracking (e.g. determining the number of forklifts). We can record data using the tracking software and it also helps us to optimize the system (e.g. warehouse optimization). 

Areas of use: 



One of the main elements of the Siemens-led Manufacturing Operations Management (MOM) portfolio product group is the Manufacturing Execution System (MES).
The Manufacturing Execution System carries out preliminary checks in five main areas:

  • Materials: whether the right materials are available.
  • Production: whether the operator is properly trained and qualified to perform the task in particular.
  • Machinery: whether the appropriate equipment is available, in the condition necessary for manufacture and with licenses for use.
  • Measurement: whether process control is ensured and whether the testing data are within the appropriate tolerance framework.
  • Methodology: whether in the process we are following the steps set out in the documentation.


Most companies that have already introduced an Enterprise Resource Planning (ERP) system can implement rough designs for weeks or even days. Today, however, it is not only necessary to be able to plan for days, but also for even smaller units of time. A successful company must respond to ever-changing needs and reschedule production in such a way that it maximizes capacity and best meets the delivery needs of customers (e.g. deadlines, quality). Our Advanced Planning and Scheduling (APS) solution can help in this in a very complex way. 


  • Automated design
  • Dynamic changes
  • Optimization algorithm
  • Intuitive user interfaces.


Optimization of the manufacturing cell in the production process supports objectives such as quality, efficiency and waste reduction. 

Optimizing the manufacturing cell and its corresponding arrangement greatly supports productivity in a production organization by grouping machines, people and other equipment used in the production process. These cells are often implemented to reduce production-related costs and to increase productivity. Many companies significantly reduce error rates even by installing cells in place. 

Collecting and analyzing operating data from production machines makes it possible to identify elementary components of OEE (Overall Equipment Effectiveness) such as availability, efficiency and quality. We can improve the OEE indicator with this solution to make the production of our manufacturing lines more efficient.


Accurate production line monitoring enables a company to maximize efficiency, capacity, improve operation, and inform and motivate its employees. This can be done by recording data directly from the production line. 

The KPI (Key Process Indicators) monitoring system shows the current status (in operation, stand-by, stopped) and productivity and quality indicators of production lines and machinery for workers in the production area. In addition, managers can see the same data and information in real-time, on both PCs and on mobile devices. It is suitable for displaying individual and public information, so it is addressable and scalable as per demand.


The lifecycle of manufacturing task management ranges from planning, testing and tracking to reporting results. Manufacturing task management systems are used to manage tasks, to facilitate estimation and scheduling, to track dependencies, resources and milestones, and to make decisions necessary to change priorities. 

This system also checks the production plan, tests capacity utilization (human resources, technology), automatically calls maintenance workers and engineers in the event of a breakdown and assigns and controls tasks. It also ensures traceability during assigned and completed tasks and measures reaction time and the time spent on the solution as well.


The predictive decision service (PDS) system is an interactive information system that analyzes large amounts of data to inform business decisions. It utilizes a combination of raw data, documents, personal knowledge, business models for users to make decisions. 

This business intelligence uses a data assessment and analysis method that can estimate business and order forecasts with an extremely high accuracy.


4The value of our 4iOP solutions lies in integrating existing technologies to create more efficient business production models. Our 4iOP solutions offer integrated industrial digitalization technologies for the following areas:

  • Manufacturing cell optimization (MCO)
  • Surveillance systems
  • Task management systems (TMS)
  • Visual analytics systems (VAS)
  • Machine-assisted forecasting systems
  • Predictive Decision Services (PDS)

Our goal is to provide production companies with a software package that can be used for a detailed analysis of the operation of manufacturing cells. The Overall Equipment Effectiveness (OEE) approach enables us to implement data collection, analysis and optimization using a method widely used in industrial practice. However, additional steps can be taken with the help of data collected in sufficient detail. The machine learning module allows the system to learn how to predict different downtimes, allowing preventive interventions as needed to help the original objective: maximizing production time.


  • Sound estimates
  • Accurate financial calculations
  • Product-related timings
  • Cell-related downtime automated measurements
  • Replacement of industrial sensors
  • Cost reduction

Key contact

Péter Gém

Business Unit Director