Maintenance has a key impact on the efficiency of the production processes because the efficiency of the machines determines the ability of the system to produce in accordance with the assumed schedule. The key element of the system performance assessment remains the availability of technological equipment, which directly translates into the efficiency and effectiveness of the performed production tasks. Taking into account the dynamic nature of manufacturing processes, the proper selection of machinery and equipment for the implementation of specific production tasks becomes an issue of particular importance. The purpose of this research was to determine the impact of technical and non-technical factors on the material selection of machine tools for production tasks and to develop a method of supporting the selection of production resources using the AHP and Fuzzy AHP methods. The research was carried out in a manufacturing company from the automotive industry.

Elaborating and applying a new model for estimating the time buffer size of a project programme, which shall guarantee a 90 % probability of timely project execution. The research included source text analysis to provide information on a research gap and the identification of the research problem. The research problem was identified: the time buffer size in a critical path programme does not guarantee a 90 % probability of timely project execution. A new model was then elaborated to estimate the buffer size; it was applied in a technical production preparation project. An additional comparative analysis was performed using the following methods to verify the model more accurately: half of the time total of a path, the sum of squares (SSQ), and the root square error method (RSEM). The application of the fuzzy model to estimate the buffer size in a critical chain programme offers can shorten the total planned project duration. It has a higher probability of timely project execution than other methods for estimating the buffer size. It guarantees a 90 % probability of timely project execution, keeping aggressive task times, which eliminates unwanted situations such as student syndrome, Parkinson’s law, overestimating task duration, and multitasking. Project programming is an inherent part of the project planning stage in project management. Recently, project management has been increasingly developing, which has been confirmed by the article’s source literature analysis. The analysis revealed a research gap in models estimating project buffer size, which might guarantee a 90 % probability of timely project execution. Thus, a fuzzy model for estimating time buffer size in a critical chain was developed, constituting added value to the science of management and quality of production engineering (currently, mechanical engineering). The fuzzy model for estimating time buffer size was applied in one Polish enterprise in a project for a new product’s technical production preparation. The fuzzy model for estimating time buffer size permits the shortening of the duration of tasks to aggressive times, guaranteeing a 90 % probability of project timely execution. The elaborated model for estimating time buffer size may be applied further in practice in projects programmed using the critical chain method.

Wydawnictwo Naukowe Uniwersytetu Szczecińskiego

The paper discusses highly important issues related to the practice of logistics project planning under conditions of certainty, risk, and uncertainty. This process requires the use of a variety of planning information (complete or incomplete, express or implied) as well as the generation of new knowledge. The decision-making process takes place in a deterministic or an nondeterministic situation; the former involves complete information (i.e., certainty) and the latter incomplete information (i.e., risk and uncertainty). Becoming acquainted with the discussed issues provides valuable practical knowledge that may be helpful in making important decisions when formulating concepts and models of logistics projects planning undertaken by a single enterprise or a supply chain.

Wydawnictwo Naukowe Uniwersytetu Szczecińskiego