International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

A practical maturity assessment is required before resource-constrained enterprises invest in smart and intelligent manufacturing. This paper proposes and demonstrates a compact method for micro and small enterprises in furniture and wood processing. Thirty questions assess fifteen capability areas grouped into People, Processes and Technologies on a 0–4 scale. Area, dimension and overall scores are complemented by a target gap and a priority index that combines business relevance and implementation complexity. A Google Sheets prototype implements transparent calculations, rule-based recommendations and an optional generative-AI layer that converts validated scores into structured initiatives. In an illustrative application to an 8–10-person furniture enterprise, the overall maturity index was 1.2/4; People scored 1.7, Processes 1.1 and Technologies 0.8. The resulting roadmap prioritizes downtime coding, production-order traceability, machine-data collection and MES-light functions before advanced analytics. The contribution is an evidence-based, dependency-constrained mechanism that converts maturity scores into prioritized and measurable transformation initiatives.

This paper presents an implemented prototype of the ontoEnMS ontology, which formalizes selected ISO 50001 energy-management knowledge and connects it with manufacturing and measurement contexts. A hybrid METHONTOLOGY/NeOn workflow is used to develop an OWL 2 DL TBox and an enterprise ABox. The model represents energy reviews, significant energy uses (SEU), energy baselines (EnB), energy performance indicators (EnPI), operational control and improvement actions. Alignment hooks connect ontoEnMS with an author-developed IEC 62264-based OntoMES model and SOSA/SSN without asserting unjustified class equivalence. The prototype is checked in Protégé 5.6.4 through HermiT/Pellet consistency reasoning and four competency questions implemented as SPARQL query patterns. An industrial mining-and-processing ABox links production units, equipment, electricity meters, observations and area-level EnPI values. For area K2-B, 18.40 kWh/t is compared with a 17.92 kWh/t baseline, identifying a 0.48 kWh/t (2.68%) adverse deviation. SHACL completeness constraints are specified as the next closed-world validation layer rather than reported as executed tests.

Cyber-physical systems (CPS) are the core of the Fourth industrial revolution and the Industry 4.0 initiative. They are facing many challenges, addressing them requires attracting and using new methods and techniques from the field of artificial intelligence and big data to make intelligent decisions and perform effective data analysis. Тhe paper presents an analyze of the current trends and challenges in the development of cyber-physical systems and the ever-increasing interest in the methods and approaches of artificial intelligence and its application in the life cycle phases of design, analysis, implementation and maintenance of CPS. There are two aspects that are the focus of attention and analysis: (1) the computing by intelligence and (2) the computing for intelligence. Finally some ideas for using different methods and approaches of artificial intelligence for achieving interoperability and autonomy of CPS are proposed.

The idea of creating and using digital twins has been strongly influenced by the process of integrating artificial intelligence methods with big data analytics of data from Internet of Things (IoT) devices. The concept of “Digital Twin” has become increasingly influential and culminating in the field of CPS. The main objective of the study is to define the basic requirements to the digital twins for cyber-physical system and based on the different definitions and components of digital twins, to summarize and analyze approaches, methods and tools used for their development. This analysis should serve as a basis for the development of a methodology for creating digital twins for cyber-physical manufacturing systems in the process industry.

The IEC-62541 (OPC UA) standard is an important part of the Industry 4.0 reference architecture and is recommended as the only possible communication standard. A particularly important issue that is being addressed is the issue of security. Cyber security is one of the most important challenges for achieving the objectives of the Industry 4.0 initiative and of the associated cyber-physical systems (CPS). The paper analyzes the vulnerability of cyber-attacks and the main threats that threaten the security of OPC UA-based CPS and defines proven and sustainable recommendations for increasing the security of these applications.

The transition to CPS is one of the great challenges of the “Industry 4.0”. The core of cyber-physical systems is an effective control, associated with achievement of a high degree of adaptability, autonomy, functionality, reliability, security and usability. The paper presents a combined approach for development of cyber-physical systems based on the IEC-61512 and IEC-61499 standards represented as partial model of asset administration shell, according the reference architectural model RAMI4.0. The models allow the description of continuous production of finite quantities of materials (batches) from two distinct views – physical and control (cyber). The approach is enhanced in respect to the correctness and reliability achieved, by replacing the semi-formal models with using of Signal Interpreted Petri Nets supporting the verification processes