PSI - Issue 81

Dmytro Voloshyn et al. / Procedia Structural Integrity 81 (2026) 228–233

231

All types of risks in the production system and their occurrences, assessment of risk probability and the effects, as well as the choice of control means are recorded in the risk register (Table 1).

Table 1. An example of the risk register for a wagon repair enterprise. No. Item Explanation 1 Risk analysis

Description of possible circumstances of risk occurrence Risk as classified at a wagon repair enterprise Structural division where the risk is identified

2 3 4 5 6 7 8 9

Type of risk

Localization of risk Risk assessment

Probability of an event and analysis of its various effects (in units, depending on the assessment methods used) Previous failures in the production system and experience in responding to their effects Selected risk management method (transfer, reduction or acceptance) Selected control mechanism and response (repair, additional control methods, etc.)

Previous experience in risk effects

Attitude to risk

Actions to reduce and control risk

Dates of events Persons in charge

Set timelines for measures to minimise negative effects Those responsible for risk control and risk mitigation in the system

The factors that contribute to the preconditions of the risk occurrence in the production system include a shortage of labour resources, low efficiency of personnel and technological resources, low reliability of technological equipment, low effectiveness of logistics systems, etc. (Table 2). This makes it possible to determine indicators of the same type. The combination of quantitative and qualitative characteristics necessitates the use of both statistical and expert-based approaches for their determination. In the present study, the indicators were determined based on operational data obtained from wagon depots over a specified period of operation.

Table 2. An example of some risk assessment indicators at the enterprise. Indicator Symbol

Algorithm

Workforce availability

A wf

N

n

1   i

i

N

100

A





ip

wf

n

Workforce efficiency

E wf Е tr

Statistical methods, expert assessment

Efficiency of technological resources

   

   

V

V



rep.perf V

f

E



tr

rep.pl

Reliability of technological equipment Efficiency of the logistics system

R te Е ls

Statistical methods, expert assessment Statistical methods, expert assessment

Where N i is the number of workers in the i-th subdivision; N іp is the planned number of workers in the i-th subdivision; n is the number of subdivisions in the enterprise; V rep.perf is the repair volume performed; V f is the volume of failures; V rep.pl is the repair volume planned according to the production capacity. The results of the research were used to determine the risk assessment indicators presented in Table 3.

Table 3. The results of the research. Indicator

Result

Unit of measure

Workforce availability Workforce efficiency

85 80 70 50 60

% % % % %

Efficiency of technological resources Reliability of technological equipment Efficiency of the logistics system

The future condition of the production system directly depends on its current condition in terms of the reliability of production processes. At a random time, the system can have one of three possible states: ● full operability (availability) means a sufficient level of necessary resources, serviceable condition of technological equipment, etc.; ● partial operability (reduced efficiency) means a lack of non-critical resources that can affect the total time of technological operations; reduced equipment efficiency due to partial failures, etc; ● fault state means that the production task cannot be fulfilled due to the lack of critical resources, emergency failure of technological equipment, etc. A well-functioning production system must have a given ratio of the planned quality to the amount of costs required. A reliable production system must ensure that the planned task is fulfilled without fail, while maintaining all production parameters at the standard level. To formalise the cause-and-effect relationships that result in the occurrence of various types of failures in a production system and affect the overall probability of risks, it is possible to use FMEA (Failure Mode and Effects Analysis) or FMECA (Failure Mode, Effect and Criticality Analysis). The input data for FMECA are the existing technological repair processes for wagons and