scholarly journals Data Analytic Approaches for Mining Process Improvement—Machinery Utilization Use Case

Resources ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 17
Author(s):  
Edyta Brzychczy ◽  
Paulina Gackowiec ◽  
Mirko Liebetrau
Keyword(s):  
Process Mining ◽  
Process Analysis ◽  
Contextual Information ◽  
Working Environment ◽  
Process Models ◽  
Working Process ◽  
Mining Operations ◽  
Data Mining Algorithms ◽  
It Systems ◽  
Roof Bolter

This paper investigates the application of process mining methodology on the processes of a mobile asset in mining operations as a means of identifying opportunities to improve the operational efficiency of such. Industry 4.0 concepts with related extensive digitalization of industrial processes enable the acquisition of a huge amount of data that can and should be used for improving processes and decision-making. Utilizing this data requires appropriate data processing and data analysis schemes. In the processing and analysis stage, most often, a broad spectrum of data mining algorithms is applied. These are data-oriented methods and they are incapable of mapping the cause-effect relationships between process activities. However, in this scope, the importance of process-oriented analytical methods is increasingly emphasized, namely process mining (PM). PM techniques are a relatively new approach, which enable the construction of process models and their analytics based on data from enterprise IT systems (data are provided in the form of so-called event logs). The specific working environment and a multitude of sensors relevant for the working process causes the complexity of mining processes, especially in underground operations. Hence, an individual approach for event log preparation and gathering contextual information to be utilized in process analysis and improvement is mandatory. This paper describes the first application of the concept of PM to investigate the normal working process of a roof bolter, operating in an underground mine. By applying PM, the irregularities of the operational scheme of this mobile asset have been identified. Some irregularities were categorized as inefficiencies that are caused by either failure of machinery or suboptimal utilization of the same. In both cases, the results achieved by applying PM to the activity log of the mobile asset are relevant for identifying the potential for improving the efficiency of the overall working process.

scholarly journals Process Modelling Based on Event Logs

2018 ◽  
Vol 1 (1) ◽  
pp. 385-392
Author(s):  
Edyta Brzychczy
Keyword(s):  
Process Management ◽  
Process Mining ◽  
Process Analysis ◽  
Process Modelling ◽  
Process Models ◽  
Sources Of Information ◽  
Event Logs ◽  
It Systems ◽  
Many Sources

Abstract Process modelling is a very important stage in a Business Process Management cycle enabling process analysis and its redesign. Many sources of information for process modelling purposes exist. It may be an analysis of documentation related directly or indirectly to the process being analysed, observations or participation in the process. Nowadays, for this purpose, it is increasingly proposed to use the event logs from organization’s IT systems. Event logs could be analysed with process mining techniques to create process models expressed by various notations (i.e. Petri Nets, BPMN, EPC). Process mining enables also conformance checking and enhancement analysis of the processes. In the paper issues related to process modelling and process mining are briefly discussed. A case study, an example of delivery process modelling with process mining technique is presented.

scholarly journals Cross-Organization Emergency Response Process Mining: An Approach Based on Petri Nets

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Cong Liu ◽  
Huiling Li ◽  
Qingtian Zeng ◽  
Ting Lu ◽  
Caihong Li
Keyword(s):  
Petri Nets ◽  
Emergency Response ◽  
Resource Sharing ◽  
Process Mining ◽  
Process Models ◽  
Response Process ◽  
Extensive Experience ◽  
Event Logs ◽  
Collaboration Patterns ◽  
Sharing Patterns

To support effective emergency disposal, organizations need to collaborate with each other to complete the emergency mission that cannot be handled by a single organization. In general, emergency disposal that involves multiple organizations is typically organized as a group of interactive processes, known as cross-organization emergency response processes (CERPs). The construction of CERPs is a time-consuming and error-prone task that requires practitioners to have extensive experience and business background. Process mining aims to construct process models by analyzing event logs. However, existing process mining techniques cannot be applied directly to discover CERPs since we have to consider the complexity of various collaborations among different organizations, e.g., message exchange and resource sharing patterns. To tackle this challenge, a CERP model mining method is proposed in this paper. More specifically, we first extend classical Petri nets with resource and message attributes, known as resource and message aware Petri nets (RMPNs). Then, intra-organization emergency response process (IERP) models that are represented as RMPNs are discovered from emergency drilling event logs. Next, collaboration patterns among emergency organizations are formally defined and discovered. Finally, CERP models are obtained by merging IERP models and collaboration patterns. Through comparative experimental evaluation using the fire emergency drilling event log, we illustrate that the proposed approach facilitates the discovery of high-quality CERP models than existing state-of-the-art approaches.

Exploring the effects of physical punishment on aggressive behavior and peer victimization: a conditional process analysis

2016 ◽  
Vol 8 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Patrik Söderberg ◽  
Kaj Bjorkqvist ◽  
Karin Österman
Keyword(s):  
Depressive Symptoms ◽  
Aggressive Behavior ◽  
Peer Victimization ◽  
Online Survey ◽  
Process Analysis ◽  
Physical Punishment ◽  
Process Models ◽  
Content Type ◽  
Conditional Process Analysis

Purpose – Recent studies indicate that exposure to physical punishment is associated with both aggressive behavior and peer victimization at school. The purpose of this paper is to explore the bidirectional relationship between aggressive behavior and peer victimization as outcomes of physical punishment, as well as the role of depressive symptoms. Design/methodology/approach – A sample of 2,424 Finnish upper primary school pupils (1,282 girls, 1,148 boys, mean age=14.2, SD=1.0) completed an online survey during class. Two conditional process models were applied using a macro for SPSS developed by Hayes (2012). Findings – Exposure to physical punishment was found to be associated with both aggressive behavior and peer victimization at school. The effect on victimization was partially mediated by aggressive behavior and depressive symptoms, whereas the effect on aggressive behavior was partially mediated by peer victimization experiences but not by depressive symptoms. The relationship between physical punishment and peer victimization was somewhat stronger for girls than for boys, but this effect was not accounted for by gender differences in depressive symptoms or aggressive behavior. Originality/value – Few studies to date have addressed the connection between aggressive behavior and peer victimization as outcomes of physical punishment. In addition, the study expands on the concept of “victim personality” by examining the mediating role of depressive symptoms. Methodologically, the study is an example of how the statistical software SPSS can be used for multiple mediation and conditional process analysis as an alternative to SEM analyses.

scholarly journals Business process mining

2017 ◽  
Vol 01 (01) ◽  
pp. 1630004 ◽  
Author(s):  
Asef Pourmasoumi ◽  
Ebrahim Bagheri
Keyword(s):  
Process Mining ◽  
Status Quo ◽  
Process Models ◽  
Added Value ◽  
Conformance Checking ◽  
Event Logs ◽  
Organizational Information ◽  
Organization Process ◽  
The Status ◽  
Business Process Mining

One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization. Process mining is an emerging area that can be useful in helping organizations understand the status quo, check for compliance and plan for improving their processes. The aim of process mining is to extract knowledge from event logs of today’s organizational information systems. Process mining includes three main types: discovering process models from event logs, conformance checking and organizational mining. In this paper, we briefly introduce process mining and review some of its most important techniques. Also, we investigate some of the applications of process mining in industry and present some of the most important challenges that are faced in this area.

scholarly journals Identifying the Absence of Effective Internal Controls: An Alternative Approach for Internal Control Audits

2018 ◽  
Vol 33 (2) ◽  
pp. 205-222 ◽  
Author(s):  
Michael Werner ◽  
Nick Gehrke
Keyword(s):  
Internal Control ◽  
Process Mining ◽  
Design Science ◽  
Study Data ◽  
Internal Controls ◽  
Process Models ◽  
Testing Procedures ◽  
Critical Data ◽  
Analysis Technique ◽  
Automated Procedures

ABSTRACT Auditors face new challenges when auditing internal controls due to the increasing integration of information systems for transaction processing and the growing amount of data. Traditional manual control testing procedures become inefficient or require highly specialized and scarce technical knowledge. This study presents audit procedures that follow a new approach. Instead of manually testing internal controls, automated procedures search for the absence of those controls. Process mining techniques are combined with advanced statistical analysis where process mining serves as a data analysis technique to create process models from the recorded transaction data. These are searched for critical data constellations in combination with an exploratory factor analysis to identify systematic deficiencies in the internal control system. The manual and time-intensive inspection of individual controls is replaced by automated audit procedures that cover the totality of recorded transactions. The study follows a design science approach and uses case study data for illustration.

scholarly journals Discovering Business Processes from Email Logs using fastText and Process Mining

2020 ◽  
Author(s):  
Yaghoub rashnavadi ◽  
Sina Behzadifard ◽  
Reza Farzadnia ◽  
sina zamani
Keyword(s):  
Machine Learning ◽  
Business Processes ◽  
Oil And Gas ◽  
Process Mining ◽  
The Body ◽  
Process Models ◽  
Supervised Machine Learning ◽  
Implicit Information ◽  
Oil And Gas Sector

<p>Communication has never been more accessible than today. With the help of Instant messengers and Email Services, millions of people can transfer information with ease, and this trend has affected organizations as well. There are billions of organizational emails sent or received daily, and their main goal is to facilitate the daily operation of organizations. Behind this vast corpus of human-generated content, there is much implicit information that can be mined and used to improve or optimize the organizations’ operations. Business processes are one of those implicit knowledge areas that can be discovered from Email logs of an Organization, as most of the communications are followed inside Emails. The purpose of this research is to propose an approach to discover the process models in the Email log. In this approach, we combine two tools, supervised machine learning and process mining. With the help of supervised machine learning, fastText classifier, we classify the body text of emails to the activity-related. Then the generated log will be mined with process mining techniques to find process models. We illustrate the approach with a case study company from the oil and gas sector.</p>

scholarly journals Towards Aspects Identification in Business Process Through Process Mining

2015 ◽  
Author(s):  
Bruna Brandão ◽  
Flávia Santoro ◽  
Leonardo Azevedo
Keyword(s):  
Programming Languages ◽  
Business Process ◽  
Process Model ◽  
Process Mining ◽  
Process Models ◽  
Preliminary Evaluation ◽  
Crosscutting Concerns ◽  
Business Process Models ◽  
Event Logs ◽  
Initial Results

In business process models, elements can be scattered (repeated) within different processes, making it difficult to handle changes, analyze process for improvements, or check crosscutting impacts. These scattered elements are named as Aspects. Similar to the aspect-oriented paradigm in programming languages, in BPM, aspect handling has the goal to modularize the crosscutting concerns spread across the models. This process modularization facilitates the management of the process (reuse, maintenance and understanding). The current approaches for aspect identification are made manually; thus, resulting in the problem of subjectivity and lack of systematization. This paper proposes a method to automatically identify aspects in business process from its event logs. The method is based on mining techniques and it aims to solve the problem of the subjectivity identification made by specialists. The initial results from a preliminary evaluation showed evidences that the method identified correctly the aspects present in the process model.

scholarly journals Digitally Enabled Health Service for the Integrated Management of Hypertension: A Participatory User-Centred Design Process

2021 ◽  
Vol 18 (23) ◽  
pp. 12442
Author(s):  
Vincenzo De De Luca ◽  
Vanja Lazic ◽  
Strahil Birov ◽  
Klaus Piesche ◽  
Ozan Beyhan ◽  
...  
Keyword(s):  
Healthcare Professionals ◽  
Healthy Lifestyle ◽  
Integrated Management ◽  
Integrated Approach ◽  
Building Blocks ◽  
Process Models ◽  
Functional Requirements ◽  
Health Care Organisation ◽  
Care Organisation ◽  
It Systems

This article describes a user-centred approach taken by a group of five procurers to set specifications for the procurement of value-based research and development services for IT-supported integrated hypertension management. The approach considered the unmet needs of patients and health systems of the involved regions. The procurers established a framework for requirements and a solution design consisting of nine building blocks, divided into three domains: service delivery, devices and integration, and health care organisation. The approach included the development of questionnaires, capturing patients’ and professionals’ views on possible system functionalities, and a template collecting information about the organisation of healthcare, professionals involved and existing IT systems at the procurers’ premises. A total of 28 patients diagnosed with hypertension and 26 professionals were interviewed. The interviewees identified 98 functional requirements, grouped in the nine building blocks. A total of nine use cases and their corresponding process models were defined by the procurers’ working group. As result, a digitally enabled integrated approach to hypertension has been designed to allow citizens to learn how to prevent the development of hypertension and lead a healthy lifestyle, and to receive comprehensive, individualised treatment in close collaboration with healthcare professionals.

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