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The purpose of this paper is comparison of experimental values of the drawing forces to numerical values in different contact conditions, taking into account the appearance of galling which occurs due to of difficult drawing process conditions.

The following two research approaches are used in this paper – the physical modeling, realized by the laboratory experiment, and the numerical simulation of the ironing drawing process. By analyzing the obtained results, the technique of physical modeling, with help of the laboratory equipment and numerical simulation by application of the finite element method, can be successfully used in studying the thin sheet ironing – strip drawing process.

It is significant to compare values of the deformation forces obtained by physical experiment to values obtained by the numerical simulation. In that way, it is possible to compare applied contact conditions (four lubricants in that case) and estimate matching of experimentally and numerically obtained results of the deformation forces. Presented results point out very good technological characteristics of ecologically friendly lubricant (single-bath) and grease based on MoS2. Significant decrease of the deformation force was achieved by its application, as well as maintaining of the lubricant’s layer during the forming process and almost complete elimination of galling on the contact.

Numerical analysis of stresses in the working piece wall, during the thin sheet strip drawing, requires precise values of the friction coefficient. It is an important indicator because one can define the contact conditions as the input data for the numerical simulation, based on its values for each type of lubricants and each value of the compressive lateral force.

The environmentally friendly lubricant tested exhibits a more favorable distribution of the drawing force during the process, mainly in experimental case. Grease based on MoS2 has good lubricating properties but that lubricant is conventional and environmentally unacceptable. Ecologically friendly lubricant can be successfully used in real ironing strip drawing process especially for high values of holding force achieving an increased tool life.

The purpose of this study is to show which filler metal is the best for hard facing. Because the quality of the surface layer has a great influence on the working life of parts, the purpose was to extend the working life of parts exposed to intensive wear. The tested hard-faced models were made of low carbon steel to save the expensive base metal and to analyze the possibilities of extending the service life of existing structural parts.

Samples were prepared from plates hard faced with various filler metals. Samples were then subjected to experimental testing – testing of tribological properties and hardness and microstructure. Testing was done in conditions similar to real ones – with a sliding speed of 0.25, 0.5 and 1 m/s and with a load of 50, 75 and 100 N and in most rigorous dry conditions. Research was done by using a combination of experimental and theoretical approaches.

The paper shows the results of the experimental testing of four different filler metals aimed for hard facing of parts exposed to highly intensive wear. Results shown that CrWC 600 alloy is the most favorable filler metal for hard facing of parts such as those of construction mechanization and those subjected to intensive abrasive wear at stone mines.

All obtained results are real and fully applicable, as there is a huge industrial need for these types of technologies. With the application of these technologies, beside money savings, the working life of parts can be significantly extended.

The research presented in this paper was conducted because of the lack of results from this area in Serbia and because of the necessity for application of obtained results in companies for road maintenance and stone excavation in the region of Šumadija, Serbia.

Socialism has institutionalised equality, guaranteeing women legal protection against abuse and discrimination. It has opened doors to women to enter public life, where in many far more developed countries women still lag behind. Nevertheless, in the domain of male‐female interaction and attitudes there has been little real change.

This paper analyses the voice of customers (VoCs) using a hybrid clustering multi-criteria decision-making (MCDM) approach. The proposed method serves as an efficient tool for how to approach multiple decision-making involving a large set of countrywide customer complaints in the Iranian automotive sector.

The countrywide data comprising 3,342 customer complaints (VoCs) were gathered. A total of seven determinant complaint criteria were identified in brainstorming sessions with three groups (six each) of experts employing the fuzzy Delphi method. The weights of these criteria were assigned by applying the fuzzy best–worst method (FBWM) to identify the severity of the complaints. Subsequently, the complaints were clustered into five categories with respective customer locations (province), car type and manufacturer using the K-mean method and further prioritised and ranked employing the fuzzy complex proportional assessment of alternatives (FCOPRAS) method.

The results indicated that the majority of complaints (1,027) from the various regions of the country belonged to one specific model of car made by a particular producer. The analyses revealed that only a few complaints were related to product quality, with the majority related to service and financial processes including delays in automobile delivery, delays in calculating monthly instalments, price variation, failure to provide a registration ( licence) and failure to supply the agreed product. The proposed method is an efficient way to solve large-scale multidimensional problems and provide a robust and reliable set of results.

The proposed method makes it much easier for management to deal with complaints by significantly reducing their number. The highest-ranked complaints from customers of the car industry in Iran are those related to delivery time, price alternations, customer service support and quality issues. Surveying the list of complaints shows that paying attention to the four most voiced complaints can reduce them more than 54%. Management can make appropriate strategies to improve the production quality as well as business processes, thus producing a significant number of customer complaints.

This paper proposes a comprehensive approach to critically analyse the VoCs by combining qualitative and decision-making approaches including K-mean, FCOPRAS, fuzzy Delphi and FBWM. This is the first paper that analyses the VoCs in the automotive sector in a developing country’s context involving large-scale decision-making problem-solving.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.