Graph-based Process Discovery containing Invisible Non-Prime Task in Procurement of Animal-Based Ingredient of Halal Restaurants

Author(s):  
Kelly Rossa Sungkono ◽  
Adhatus Solichah Ahmadiyah ◽  
Riyanarto Sarno ◽  
Muhammad Farhan Haykal ◽  
Muhammad Rayhan Hakim ◽  
...  
Keyword(s):  
Author(s):  
Renato Cirne ◽  
Caio Melquiades ◽  
Renan Leite ◽  
Eronita Leijden ◽  
Alexandre Maciel ◽  
...  

2020 ◽  
Vol 34 (06) ◽  
pp. 10218-10225 ◽  
Author(s):  
Fabrizio M Maggi ◽  
Marco Montali ◽  
Rafael Peñaloza

Temporal logics over finite traces have recently seen wide application in a number of areas, from business process modelling, monitoring, and mining to planning and decision making. However, real-life dynamic systems contain a degree of uncertainty which cannot be handled with classical logics. We thus propose a new probabilistic temporal logic over finite traces using superposition semantics, where all possible evolutions are possible, until observed. We study the properties of the logic and provide automata-based mechanisms for deriving probabilistic inferences from its formulas. We then study a fragment of the logic with better computational properties. Notably, formulas in this fragment can be discovered from event log data using off-the-shelf existing declarative process discovery techniques.


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Shabnam Shahzadi ◽  
Xianwen Fang ◽  
David Anekeya Alilah

For exploitation and extraction of an event’s data that has vital information which is related to the process from the event log, process mining is used. There are three main basic types of process mining as explained in relation to input and output. These are process discovery, conformance checking, and enhancement. Process discovery is one of the most challenging process mining activities based on the event log. Business processes or system performance plays a vital role in modelling, analysis, and prediction. Recently, a memoryless model such as exponential distribution of the stochastic Petri net SPN has gained much attention in research and industry. This paper uses time perspective for modelling and analysis and uses stochastic Petri net to check the performance, evolution, stability, and reliability of the model. To assess the effect of time delay in firing the transition, stochastic reward net SRN model is used. The model can also be used in checking the reliability of the model, whereas the generalized stochastic Petri net GSPN is used for evaluation and checking the performance of the model. SPN is used to analyze the probability of state transition and the stability from one state to another. However, in process mining, logs are used by linking log sequence with the state and, by this, modelling can be done, and its relation with stability of the model can be established.


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