Datengetriebene Steigerung der Verfügbarkeit/Data-supported root cause analysis to increase the availability of machine tools. Data-driven availability increase

2020 ◽  
Vol 110 (07-08) ◽  
pp. 532-535
Author(s):  
Eckhart Uhlmann ◽  
Roman Dumitrescu ◽  
Julian Polte ◽  
Maurice Meyer ◽  
Deniz Simsek
Keyword(s):  
Data Analysis ◽  
Machine Tools ◽  
Critical Factor ◽  
Root Cause Analysis ◽  
Data Driven ◽  
Manufacturing Companies ◽  
Cause Analysis ◽  
Root Cause ◽  
Comprehensive Data ◽  
Causes Of Failure

Die Zuverlässigkeit von Werkzeugmaschinen ist ein kritischer Faktor für den Erfolg produzierender Unternehmen. Durch die Analyse von Daten in der Produktplanung können Maschinenhersteller Ausfallursachen eliminieren und Maschinen systematisch verbessern. Jedoch stellt eine umfassende Datenanalyse viele Unternehmen vor große Herausforderungen. Die in diesem Beitrag vorgestellte Methodik adressiert diese Problematik und unterstützt Unternehmen bei der zielgerichteten Datenanalyse.   The reliability of machine tools is a critical factor for the success of manufacturing companies. By analyzing data in product planning, machine manufacturers can eliminate causes of failure and systematically improve machines. However, comprehensive data analysis poses great challenges for many companies. The methodology presented in this paper addresses this problem and supports companies in the goal-driven data analysis.

Automated Bug Hunting With Data-Driven Symbolic Root Cause Analysis

2021 ◽  
Author(s):  
Carter Yagemann ◽  
Simon P. Chung ◽  
Brendan Saltaformaggio ◽  
Wenke Lee
Keyword(s):  
Root Cause Analysis ◽  
Data Driven ◽  
Cause Analysis ◽  
Root Cause

Slug Flow Root Cause Analysis: A Data-Driven Approach

2019 ◽  
Author(s):  
Anders T. Sandnes ◽  
Vidar Uglane ◽  
Bjarne Grimstad
Keyword(s):  
Slug Flow ◽  
Root Cause Analysis ◽  
Data Driven ◽  
Cause Analysis ◽  
Root Cause ◽  
Data Driven Approach

scholarly journals Prioritisation of root cause analysis in production disturbance management

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Adriana Soares Ito ◽  
Torbjörn Ylipää ◽  
Per Gullander ◽  
Jon Bokrantz ◽  
Anders Skoogh
Keyword(s):  
Root Cause Analysis ◽  
Resource Utilisation ◽  
Manufacturing Companies ◽  
Cause Analysis ◽  
Content Type ◽  
Root Cause ◽  
Wide Range ◽  
Disturbance Management ◽  
Machine Health ◽  
Process Perspective

PurposeManufacturing companies struggle to manage production disturbances. One step of such management deals with prioritising those disturbances which should undergo root cause analysis. The focus of this work is on two areas. First, investigating current challenges faced by manufacturing companies when prioritising root cause analysis of production disturbances. Second, identifying the stakeholders and factors impacted by production disturbances. Understanding the current challenges and identifying impacted stakeholders and factors allows the development of more efficient prioritisation strategies and, thus, contributes to the reduction of frequency and impact of disturbances.Design/methodology/approachTo achieve the intended purpose of this research, a qualitative approach was chosen. A series of interviews was conducted with practitioners, to identify current challenges. A series of focus groups was also held, to identify the impacted stakeholders and factors by disturbances.FindingsVarious challenges were identified. These are faced by manufacturing companies in their prioritisation of production disturbances and relate to the time needed, criteria used, centralisation of the process, perspective considered and data support. It was also found that a wide range of stakeholders is impacted by production disturbances, surpassing the limits of production and maintenance departments. Furthermore, the most critical factors impacted are quality, work environment, safety, time, company results, customer satisfaction, productivity, deliverability, resource utilisation, profit, process flow, plannability, machine health and reputation.Originality/valueThe current situation regarding root cause analysis prioritisation has not been identified in previous works. Moreover, there has been no prior systematic identification of the various stakeholders and factors impacted by production disturbances.

scholarly journals Monitoring Process Variability and Root Cause Analysis in Paper Box Production

2018 ◽  
Vol 7 (4.30) ◽  
pp. 492
Author(s):  
Rohayu Mohd Salleh ◽  
Ng Jin Chuan ◽  
Sabariah Saharan
Keyword(s):  
Root Cause Analysis ◽  
Manufacturing Companies ◽  
Process Variability ◽  
Cause Analysis ◽  
Root Cause ◽  
Computation Efficiency ◽  
Analysis Technique ◽  
Monitoring Procedure ◽  
Multiple Characteristics ◽  
T2 Control Chart

In this paper, monitoring procedure for process variability in multivariate setting based on individual observations which is a combination of (i) Hotelling’s T2 control chart in detecting out of control signal and (ii) implementation of Mason, Young and Tracy (MYT) decomposition and structure analysis technique for root cause analysis is introduced. The advantages of this procedure will be shown by using the case of a paper box production process in one of the Malaysian manufacturing companies. The successful application of this multivariate approach could act as a stimulant for most industries to imitate in process monitoring. Moreover, the computation efficiency in root cause analysis enables quality’s multiple characteristics to be monitored simultaneously. Based on the findings, the core issue that needs to be a matter of concern by the management team is the closure tap of the box. This process variation should be solved immediately to avoid the products’ quality from further deteriorating.

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