Supply Chain Management (SCM) is a very important part of the industrial world, especially in the manufacturing sector. The development of the business world affects the complexity of the supply chain due to the lack of logistics infrastructure, quality of materials and components, and much more. Supply chain disruption risk mapping needs to be done due to high uncertainty, which is overcome by implementing a decision support system. Based on the background of the problem, supply chain disruption mapping uses the help of the Six Sigma method, which consists of 5 stages: Define, Measure, Analyze, Improve, and Control (DMAIC). The measurement of disturbance also uses the Failure Mode and Effect Analysis (FMEA) approach to prioritize risk. Risks that have a high assessment and cause failure need to be prioritized for improvement. This study aims to map supply chain disruptions in the current manufacturing industry based on the barriers, resistances, and causes detected for making a decision support system prototype. By implementing a decision support system in the supply chain process, it is

FMEAs have been prioritized using RPN; however, a new standard has introduced AP for prioritization. This study seeks to determine if the number of required improvement actions increases, decreases, or stays the same when using AP in place of RPN. Statistical software was used to simulate 10,000 combinations of severity, occurrence, and detection. Both AP and RPN were calculated for the 10,000 combinations. Statistical hypothesis testing was performed to determine if there was a difference between RPNs when sorted by AP and to determine if there was a difference in actions required using RPN or AP. There is a statistically significant difference between RPNs when sorted by high, medium, and low AP. Using an RPN threshold equal to or greater than 100 would result in no change in the number of actions required if prioritizing by high and medium, but would result in fewer actions required if only high is used.

Horizontal Directional Drilling (HDD) technology is a highly complex process connected with high risk and uncertainty due the high variability underground strata, often limited access to specialised equipment, dynamic natural environment, technical disruptions, human factor and changes in economic environment that further complicate the gathering of reliable information and data. This work presents a new risk evaluation model tailored for HDD technology, in which failure mode and effect analysis (FMEA) modelling were applied. This paper focuses on 15 human risk factors and 9 equipment risk factors in HDD technology. The proposed approach takes into account not only the probability of the risk factor occurrence, but also its severity and the possibility of detecting faults, which were not clearly separated and analyzed in the previous works. Application of the proposed model shows the relationship between occurrence, severity and detection for the analyzed failures. Moreover, many detection possibilities for the identified failures were presented. The calculated risk priority numbers allowed to rank HDD failures and identify the most critical risks for which one should look for risk treatment possibilities beyond risk cause reduction, such as risk effect reduction, risk transfer, risk elimination or active risk retention.

The article presents the possibility of increasing the production efficiency in an enterprise dealing in the production of lounge furniture. The literature review shows that Poland is the sixth country in the world in the amount of furniture production. It is also one of the leading exporters of upholstered furniture in Europe. Each year, the value of furniture sales production increases by a few percentage points. Due to the constantly growing customer orders, many companies in this industry are struggling with delays in delivering products to customers. This problem also occurs in the analyzed company. While analyzing the production process, the occurrence of a large number of non-conformities was also noticed. An analysis was carried out to indicate the number of non-conformities and the place of their occurrence. The FMEA analysis was used, which indicated which non-conformities are the most important, and the 5Why method, which allowed to indicate the cause of their occurrence. The analysis of production processes showed which activities do not bring added value and how they can be eliminated at no cost. All these measures contributed to increasing the efficiency of the production of lounge furniture.

The FMEA (Failure Mode and Effects Analysis) method consists in analysis of failure modes and evaluation of their effects based on

determination of cause-effect relationships for formation of possible product or process defects. Identified irregularities which occur

during the production process of piston castings for internal combustion engines were ordered according to their failure rates, and using

Pareto-Lorenz analysis, their per cent and cumulated shares were determined. The assessments of risk of defects occurrence and their

causes were carried out in ten-point scale of integers, while taking three following criteria into account: significance of effects of the defect

occurrence (LPZ), defect occurrence probability (LPW) and detectability of the defect found (LPO). A product of these quantities

constituted the risk score index connected with a failure occurrence (a so-called “priority number,” LPR). Based on the observations of the

piston casting process and on the knowledge of production supervisors, a set of corrective actions was developed and the FMEA was

carried out again. It was shown that the proposed improvements reduce the risk of occurrence of process failures significantly, translating

into a decrease in defects and irregularities during the production of piston castings for internal combustion engines.

Horizontal Directional Drilling (HDD) is a very complex technology. Although the installation of pipelines by means of this technology is often successful, examples of unsuccessful projects are also known. Due to the complexity of the technology, with the interaction of multiple processes, risks related to uncertainties in these processes play important role. These risks are related to the variability of underground strata, changing natural environment, changes in economic environment, as well as limitations of the equipment, technical disruptions and human factors. This paper describes the risk evaluation results of the FMEA and a Pareto– Lorenz analysis for 14 external risk factors (8 natural or environmental risk factors as well as 6 economic risk factors) in HDD technology. In the proposed approach not only the probability of the external risk factor occurrence was considered, but also its consequences and the ability to detect faults, which were not plainly separated and taken into account in the literature so far. Such an approach has shown the relationship between occurrence, severity and detection for the analysed external failures. Moreover, 40 detection possibilities for the external risks in HDD technology were identified. The calculated risk priority numbers enabled ranking HDD external failures and identified the most critical risks for which the suggested detection options were unsatisfactory and insufficient, and therefore other types of risk response actions need to be explored.