Andrea Sujová, Katarína Marcineková and Ľubica Simanová
internal processes should be determined in a way that enables to monitor the fulfilment of corporate key result indicators or strategic key success factors. This is the reason why the literature review of the article focused on this part of the business process measurement.
Modern management approaches require using modern methods and indicators for performance evaluation. The interconnection between processperformance measurement and corporate performance evaluation has not been addressed in scientific publications. Most of the scientific works deal with corporate
Krzysztof Jarosz, Piotr Niesłony and Piotr Löschner
In this article, a novel approach to computer optimization of CNC toolpaths by adjustment of cutting speed vcand depth of cut apis presented. Available software works by the principle of adjusting feed rate on the basis of calculations and numerical simulation of the machining process. The authors wish to expand upon this approach by proposing toolpath optimization by altering two other basic process parameters. Intricacies and problems related totheadjustment of apand vcwere explained in the introductory part. Simulation of different variant of the same turning process with different parameter values were conducted to evaluate the effect of changes in depth of cut and cutting speed on process performance. Obtained results were investigated on the account of cutting force and tool life. The authors have found that depth of cut substantially affects cutting force, while the effect of cutting speed on it is minimal. An increase in both depth of cut and cutting speed affects tool life negatively, although the impact of cutting speed is much more severe. An increase in depth of cut allows for a more significant reduction of machining time, while affecting tool life less negatively. On the other hand, the adjustment of cutting speed helpsto reduce machining time without increasing cutting force component values and spindle load.
, V., 2011. Improved planning in the automotive industry - Advanced product quality planning , Festival of Quality - FQ 2011, Kragujevac, Serbia, A84-A90.
Radlovački, V., 2007. The general model of monitoring and evaluation of the quality management system effectivity , Faculty of technical Sciences, Novi Sad, Serbia. (in: Serbian)
Simeunović, B.P., 2015. Development of processperformance measurement model , Doctoral Dissertation, University of Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia. (in: Serbian)
Smook, G.A., 2003
Erika Škvareková, Marianna Tomašková, Gabriel Wittenberger and Štefan Zelenák
and Energy , 2008, 222, (A7), Special Issue.
 Laciak, M., Kostúr, K., Durdán, M., Kačur, J., Flegner, P. The analysis of the underground coal gasification in experimental equipment, Energy, 2016, 114, 332-343.
 Perkins, G. Underground coal gasification – Part I: Field demonstrations and processperformance, Progress in Energy and Combustion Science , 2018, 67, 158-187.
 Taušová, M., Rybárová J., Khouri S. Financial analysis, as a marketing tool in the process of raising awareness on renewable energy, Acta Montanistica Slovaca , 2007
Andrea Sujová, Ľubica Simanová and Katarína Marcineková
Oeconomia , 3 (2), 65–79.
Implementation of optimization methods in the selected areas of production logistics
Forum Scientiae Oeconomia
Sujová, A., Simanová, Ľ., & Marcineková, K. (2016). Sustainable ProcessPerformance by Application of Six Sigma Concepts: The Research Study of Two Industrial Cases. Sustainability, 8 (3), 260. doi: 10.3390/su8030260
Sustainable ProcessPerformance by Application of Six Sigma Concepts: The Research Study
Technology 23 1 1 11
Sujová, A., Marcineková, K., & Simanová, Ľ. (2019). Influence of Modern ProcessPerformance Indicators on Corporate Performance — the Empirical Study. Engineering Management in Production and Services 11(2), 119-129. doi: 10.2478/emj-2019-0015 10.2478/emj-2019-0015 Sujová A. Marcineková K. Simanová Ľ. 2019 Influence of Modern ProcessPerformance Indicators on Corporate Performance — the Empirical Study Engineering Management in Production and Services 11 2 119 129 10.2478/emj-2019-0015
Tsai, P. (1989). Variable
, 2 , 1-21.
Rut, J. (2017). Production Process Optimization in the Researched Company. Marketing i Rynek , 7 , 625-633.
Simanová, Ľ., & Gejdoš, P. (2015). The Use of Statistical Quality Control Tools to Quality Improving in the Furniture Business. Procedia Economics and Finance , 34 , 276-283. doi: 10.1016/S2212-5671(15)01630-5
Sujova, A., & Marcinekova, K. (2014). The Impact of Using Modern ProcessPerformance Indicators on Financial Perormance of Woodworking Companies. Management of Companies , 4 (1), 30-35.
Sujova, A., & Marcinekova
in sigma units and is known as the process capability. The process capability measurement index is the processperformance index (Ppk). Once a process has been brought under statistical control through the implementation of a Six Sigma project, Ppk estimates how stable these improvements would be in the longterm and how closely they would meet customer expectations. The larger the Ppk value, the less is the process variability and the higher the long-term stability. To satisfy customers, the Ppk value should be greater than 1.67 ( Kotz, 1993 ; Raman & Basavaraj
attributes of particular indicators by means of the Z-MESOT method can help eliminate problems resulting in incorrectly defined responsibilities and powers in the course of measurement and performance evaluation processes.
Performance and measurement responsibilities were explicitly defined in most key performance indicators. Managers positively evaluated a combination of suggested indicators that cover key business performance areas. Competent managers express their opinion that measuring and evaluating performance for them is a necessary tool for successful corporate