576
As is the case with Data Governance, the SOA Governance policy assumes the creation
of many organisational roles and support for tasks related to maintaining services of an
appropriate standard. As a consequence, it enables the implementation of business processes.
Clients of the service can search the repository to use a service of their choice. Analysts and
architects design new services and modify current ones. Programmers write a code responsible for the implementation of the business process. Administrators ensure that services are
secure and available. Business owners of the services supervise them.
4.3 A proposed extension of the IT system architecture model at KGHM Polska Miedź
based on big data tools
The IT system architecture model at KGHM Polska Miedź discussed in the previous section, enables efficient handling of business processes in terms of storage, processing, analysis,
integration, and making data available in the form of reports. The scope of data is limited
to thematic warehouses. The amount of data is relatively small, and data loading processes
usually take place once a day (or more frequently, in individual cases).
The demand for the collection and processing of large amounts of data in real time is
expected to increase in the near future due to ongoing and planned projects. There is discussion on the implementation of new systems in the field of mining, mechanics, geology (geodesy) or the widely understood concept of IOT (Internet of Things) (Perry, L. 2018) related
to the handling and analysis of data from industrial equipment (water pumps, sensors of
self-propelled mining machines, belt conveyors, sensors of seismic vibrations, etc.). In addition to typical structural data, there is also a need to collect unstructured data, such as images
from CCTV cameras or sounds produced by rock masses or machinery. To analyse this type
of data, we could employ algorithms, methods and tools of artificial intelligence (Ford, M.
2018), data mining (Han, J. & Kamber, M. 2006), and machine learning (Dean, J. 2014). They
are able to process and analyse signals (e.g. image recognition) in real time and, on that basis,
to take appropriate decision-making steps. A decision-making system may be helpful in such
a case by sending a message to a device (e.g. an air-conditioning fan) about its stoppage while
simultaneously notifying relevant services (report, e-mail, text message, etc.).
The extension of the IT system architecture model at KGHM Polska Miedź by adding new
Big Data tools does not interfere with the implementation of Data Governance and SOA
Governance principles. After the model has been extended with Big Data tools, processes and
people will be supervised by these solutions.
5 CONCLUSIONS
The challenges posed by the Industry 4.0 concept make companies introduce appropriate
organisational, legal, and technological changes. In the several years to come, the implementation of the Industry 4.0 concept will constitute a “to be or not to be” case. It allows not only
to gain a competitive advantage, but it is also the foundation of a stable company. KGHM
Polska Miedź certainly aspires to be one of the companies aiming at full compliance with
the concept of Industry 4.0. The first steps have been taken, which is reflected in the launch
of the KGHM 4.0 Programme, comprising many key projects implemented in various areas
of the company’s operation. This article sets out to present plans to build a data and service management centre as one of the main elements of Platform 4.0. The work has already
started on two projects: “SOA-oriented architecture” and “Development of Data Governance processes, including policies and standards for data processed within business areas”.
Plans for the first stage involve implementing mainly analytical tools, while the second phase
will consist in introducing Big Data tools that will enable the analysis of industrial data as
well as the processing of data from sources including spatial information systems.
In accordance with the guidelines of the Data Governance and SOA Governance concepts, tasks related to the implementation of IT tools, procedures and organisational changes
are performed. The result of this work is expected to be an environment enabling efficient
As is the case with Data Governance, the SOA Governance policy assumes the creation
of many organisational roles and support for tasks related to maintaining services of an
appropriate standard. As a consequence, it enables the implementation of business processes.
Clients of the service can search the repository to use a service of their choice. Analysts and
architects design new services and modify current ones. Programmers write a code responsible for the implementation of the business process. Administrators ensure that services are
secure and available. Business owners of the services supervise them.
4.3 A proposed extension of the IT system architecture model at KGHM Polska Miedź
based on big data tools
The IT system architecture model at KGHM Polska Miedź discussed in the previous section, enables efficient handling of business processes in terms of storage, processing, analysis,
integration, and making data available in the form of reports. The scope of data is limited
to thematic warehouses. The amount of data is relatively small, and data loading processes
usually take place once a day (or more frequently, in individual cases).
The demand for the collection and processing of large amounts of data in real time is
expected to increase in the near future due to ongoing and planned projects. There is discussion on the implementation of new systems in the field of mining, mechanics, geology (geodesy) or the widely understood concept of IOT (Internet of Things) (Perry, L. 2018) related
to the handling and analysis of data from industrial equipment (water pumps, sensors of
self-propelled mining machines, belt conveyors, sensors of seismic vibrations, etc.). In addition to typical structural data, there is also a need to collect unstructured data, such as images
from CCTV cameras or sounds produced by rock masses or machinery. To analyse this type
of data, we could employ algorithms, methods and tools of artificial intelligence (Ford, M.
2018), data mining (Han, J. & Kamber, M. 2006), and machine learning (Dean, J. 2014). They
are able to process and analyse signals (e.g. image recognition) in real time and, on that basis,
to take appropriate decision-making steps. A decision-making system may be helpful in such
a case by sending a message to a device (e.g. an air-conditioning fan) about its stoppage while
simultaneously notifying relevant services (report, e-mail, text message, etc.).
The extension of the IT system architecture model at KGHM Polska Miedź by adding new
Big Data tools does not interfere with the implementation of Data Governance and SOA
Governance principles. After the model has been extended with Big Data tools, processes and
people will be supervised by these solutions.
5 CONCLUSIONS
The challenges posed by the Industry 4.0 concept make companies introduce appropriate
organisational, legal, and technological changes. In the several years to come, the implementation of the Industry 4.0 concept will constitute a “to be or not to be” case. It allows not only
to gain a competitive advantage, but it is also the foundation of a stable company. KGHM
Polska Miedź certainly aspires to be one of the companies aiming at full compliance with
the concept of Industry 4.0. The first steps have been taken, which is reflected in the launch
of the KGHM 4.0 Programme, comprising many key projects implemented in various areas
of the company’s operation. This article sets out to present plans to build a data and service management centre as one of the main elements of Platform 4.0. The work has already
started on two projects: “SOA-oriented architecture” and “Development of Data Governance processes, including policies and standards for data processed within business areas”.
Plans for the first stage involve implementing mainly analytical tools, while the second phase
will consist in introducing Big Data tools that will enable the analysis of industrial data as
well as the processing of data from sources including spatial information systems.
In accordance with the guidelines of the Data Governance and SOA Governance concepts, tasks related to the implementation of IT tools, procedures and organisational changes
are performed. The result of this work is expected to be an environment enabling efficient