A Data Model to Apply Process Mining in End-to-End Order Processing Processes of Manufacturing Companies

Die Fähigkeit der additiven Fertigung in Losgröße 1 zu fertigen, erzeugt eine hohe Komplexität in der Auftragsabwicklung. Dies stellt die datenbasierte Optimierung der Prozessabläufe vor große Herausforderungen. Durch die geringen Stückzahlen, bei einer hohen Variantenanzahl, ist die Prozessaufnahme in der additiven Fertigung mit signifikanten Aufwänden verbunden. Abhilfe kann hier eine automatisierte Prozessaufnahme schaffen. Deshalb soll in diesem Beitrag die Technologie des Process Mining untersucht und darauf aufbauend eine Vorgehensweise für die datenbasierte Optimierung in der additiven Fertigung vorgestellt werden.   The capability of additive manufacturing to produce in batch size 1 creates a high degree of complexity in order processing. This creates great challenges for the data-based optimization of process flows. Due to the low number of pieces, with a high number of variants, the process recording in additive manufacturing is connected with significant expenditures. This can be overcome by automated process recording. Therefore, this article will examine the technology of process mining and, based on this, present a procedure for data-based optimization in additive manufacturing.

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Produktionsplanung in RMS/Production Planning in RMS - System for Production Process Planning in Reconfigurable Manufacturing Systems (RMS)

wt Werkstattstechnik online ◽

10.37544/1436-4980-2015-04-51 ◽

2015 ◽

Vol 105 (04) ◽

pp. 209-214

Author(s):

A. Hees ◽

K. Zellner ◽

G. Reinhart

Keyword(s):

Production Planning ◽

Process Planning ◽

Data Model ◽

Manufacturing Systems ◽

Reconfigurable Manufacturing Systems ◽

Reconfigurable Manufacturing ◽

Manufacturing Companies ◽

New Approach ◽

Short Intervals ◽

Dynamic Markets

Zur Sicherung der Wettbewerbsfähigkeit in dynamischen Märkten müssen produzierende Unternehmen ihre Produktionssysteme in häufigen Intervallen anpassen. Ein Ansatz, diesen Herausforderungen zu begegnen, sind rekonfigurierbare Produktionssysteme (englisch: Reconfigurable Manufacturing Systems – RMS). Vorgestellt wird ein neuer Ansatz für die Produktionsplanung und -steuerung (PPS) in RMS – bestehend aus einem Datenmodell, einem Konfigurationsmanagement und einer Planungsmethode.   Manufacturing companies have to adapt their manufacturing systems in frequent and short intervals to secure their competitiveness in dynamic markets. One approach to ensure companies’ success are Reconfigurable Manufacturing Systems (RMS). In this context, a new approach for production planning (PPC) in RMS, consisting of a data model, a configuration management and a planning method, is described in this paper.

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Data-based description of process performance in end-to-end order processing

CIRP Annals ◽

10.1016/j.cirp.2020.03.013 ◽

2020 ◽

Vol 69 (1) ◽

pp. 381-384 ◽

Cited By ~ 1

Author(s):

Günther Schuh ◽

Andreas Gützlaff ◽

Seth Schmitz ◽

Wil M.P. van der Aalst

Keyword(s):

Process Performance ◽

Order Processing ◽

End To End

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End-to-End provenance representation for the understandability and reproducibility of scientific experiments using a semantic approach

Journal of Biomedical Semantics ◽

10.1186/s13326-021-00253-1 ◽

2022 ◽

Vol 13 (1) ◽

Author(s):

Sheeba Samuel ◽

Birgitta König-Ries

Keyword(s):

Data Model ◽

Biological Imaging ◽

Computational Science ◽

Semantic Approach ◽

Computational Data ◽

Scientific Experiments ◽

End To End ◽

Computational Processes ◽

Processing Steps ◽

Complete Path

Abstract Background The advancement of science and technologies play an immense role in the way scientific experiments are being conducted. Understanding how experiments are performed and how results are derived has become significantly more complex with the recent explosive growth of heterogeneous research data and methods. Therefore, it is important that the provenance of results is tracked, described, and managed throughout the research lifecycle starting from the beginning of an experiment to its end to ensure reproducibility of results described in publications. However, there is a lack of interoperable representation of end-to-end provenance of scientific experiments that interlinks data, processing steps, and results from an experiment’s computational and non-computational processes. Results We present the “REPRODUCE-ME” data model and ontology to describe the end-to-end provenance of scientific experiments by extending existing standards in the semantic web. The ontology brings together different aspects of the provenance of scientific studies by interlinking non-computational data and steps with computational data and steps to achieve understandability and reproducibility. We explain the important classes and properties of the ontology and how they are mapped to existing ontologies like PROV-O and P-Plan. The ontology is evaluated by answering competency questions over the knowledge base of scientific experiments consisting of computational and non-computational data and steps. Conclusion We have designed and developed an interoperable way to represent the complete path of a scientific experiment consisting of computational and non-computational steps. We have applied and evaluated our approach to a set of scientific experiments in different subject domains like computational science, biological imaging, and microscopy.

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Research on Influencing Factors of Manufacturing Listed Companies’ Working Capital Policy in China

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1028.111 ◽

2014 ◽

Vol 1028 ◽

pp. 111-116

Author(s):

Qiang Hu ◽

You Qing Wan ◽

Jie Qiong Wang

Keyword(s):

Panel Data ◽

Data Model ◽

Economic Activity ◽

Social Economic ◽

Listed Company ◽

Panel Data Model ◽

Internal Environment ◽

Manufacturing Companies ◽

Working Capital ◽

Factors Affecting

At present, the majority of the researches on factors affecting policies of listed company working capital mainly focus on internal environment, which result in the ignorance of the outside condition. However, as the major participant for social economic activity companies, the outside situation will definitely have an influence on the formulation of working capital policy. Therefore, basing on former studies, this paper comprehensively combines inner factors with outside ones, and selects the data from long-standing manufacturing companies, and applies the panel data model in order to figure out how these factors work on companies’ working capital policy.

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Understanding Process Mining for Data-Driven Optimization of Order Processing

Procedia Manufacturing ◽

10.1016/j.promfg.2020.04.046 ◽

2020 ◽

Vol 45 ◽

pp. 417-422

Author(s):

Günther Schuh ◽

Andreas Gützlaff ◽

Sven Cremer ◽

Marco Schopen

Keyword(s):

Process Mining ◽

Data Driven ◽

Order Processing

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Pengaruh Modified Audit Opinion terhadap Financial Constraint

JURNAL EKSPLORASI AKUNTANSI ◽

10.24036/jea.v1i4.172 ◽

2019 ◽

Vol 1 (4) ◽

pp. 1723-1740

Author(s):

Ilham Yahya ◽

Nurzi Sebrina

Keyword(s):

Data Model ◽

Financial Constraints ◽

Sampling Method ◽

Stock Exchange ◽

Financial Constraint ◽

Manufacturing Companies ◽

Audit Opinion ◽

Accounting Principles ◽

Independent Variable ◽

Audit Opinions

This study aims to investigate and find empirical evidence whether companies that get modified audit opinions tend to be easy or difficult to get funding from outside the company and prove the effect of modified audit opinions on financial constraints. This study uses a panel data model with random effects and is a quantitative study with a hypothesis. The population in this study is manufacturing companies listed on the Indonesia Stock Exchange in 2014-2017. The method used in determining the sample is purposive sampling method. Based on these criteria, as many as 50 companies were selected as samples with a total of observations over four years of 200 firm-years. The independent variable in this study is financial constraint, while the dependent variable is modified audit opinions. The control variables in this study are Size, Leverage, and Growth. The results of the study indicate that Modified audit opinion does not significantly influence financial constraints, meaning Modified audit opinion obtained by the company is not proven to affect the ability of the company to obtain loans. This means that audit opinion does not affect the decision of creditors to provide loans. However, of all types of Modified audit opinions, only an unqualified opinion with an explanatory paragraph about the inconsistency of accounting principles and going concern that negatively affects the decision of creditors in lending.

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