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Modern manufacturing systems generate large amounts of data regarding the automation of business processes, which can be analyzed with process mining techniques. However, there is not enough consolidation on process mining methodologies or guidelines on properly applying numerous techniques in particular manufacturing scenarios. This paper aims to synthesize data on process mining projects' goals, utilize information systems, analyze business processes, and apply process mining types, software tools, and algorithms applied in the manufacturing industry. The data on the key research elements are gathered through a systematic literature review and analyzed with descriptive statistics and crosstabs analysis in SPSS. The research results enable process mining practitioners, business analysts, and business managers to gain insight into the trends and benefits of process mining application in the manufacturing context, as well as a guideline on how process mining techniques can be applied depending on the analyzed business process and process mining projects' goal. © INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING