The dyeing domain is a dynamic, complex and involved various discipline. The dyeing process is difficult to automate processes, because of their interdisciplinary and dynamic in nature. Moreover, it is also critical to keep a check on the automated processes to produce the expected results in the form of quality and timely dyeing processes. Delivering these processes is a complex, because colour shades are generally new, and tend to have complex dye mix problems. The drive in dyeing

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... s is to reduce costs and at the same time improve the quality of colours the shades need. The benefit of workflow management systems in such domain includes cost reduction, improved operational efficiencies, pH test error reduction, improved shade quality, better communication and collaboration and real time audit of processes. Hence, such systems need a process model and this process model should clearly depict the control flow of the tasks in any type of dyeing process. Therefore the focus of this paper is on the process discovery. For this a plug-in implemented in ProM Framework has been used, for this HM algorithm and DWS algorithm. This study also evaluates the HM and DWS mining algorithms, which may have a major impact on the future development of efficient process mining algorithms.