Beitrag zur modellbasierten Bewertung der Komplexität in der Montagelogistik der Automobilindustrie
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Date
2018
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Abstract
Die Automobilindustrie wurde in den letzten Jahren durch vielfältige Herausforderungen geprägt, wodurch insbesondere die Logistik aufgrund ihrer Querschnittsfunktion betroffen ist. Globalisierung, verändertes Nachfrageverhalten und eine höhere Marktheterogenität führten zu einer substantiellen Ausweitung der Modellpalette, während sich gleichzeitig, begründet durch eine höhere Marktdynamik, die Entwicklungszyklen drastisch verkürzt haben. Durch die Notwendigkeit immer mehr Modelle in bestehende Werksstrukturen integrieren und deren Versorgung sicherstellen zu müssen, sieht sich vor allem die Logistik mit einem steigenden Komplexitätsniveau konfrontiert. Die Logistiknetzwerke sind heutzutage geprägt durch eine große Anzahl, Vielfalt und Dynamik der Netzwerkpartner. Aufgrund der Größe und des hohen Vernetzungsgrads erscheinen diese Netzwerke unübersichtlich und komplex. Der zunehmende Trend des global sourcings verstärkt diesen Effekt zusätzlich. In den kommenden Jahren wird im Zuge der zunehmenden Bedeutung von Elektromobilität, Digitalisierung und Vernetzung ein weiterer Komplexitätsanstieg erwartet.
Es ist bisher jedoch nicht möglich diese Komplexitätszuwächse zu quantifizieren und fundierte Aussagen über deren Auswirkungen auf den Logistikerfolg zu treffen. Daher wird in dieser Arbeit zunächst Transparenz über die komplexitätstreibenden Faktoren in der Montagelogistik geschaffen, um darauf aufbauend eine Bewertungsmethodik für Logistikkomplexität zu entwickeln. Dafür werden zunächst, aufbauend auf einer Literatur-recherche, im Rahmen einer qualitativen Studie leitfadengestützte Experteninterviews durchgeführt, um die relevanten Komplexitätstreiber in der Montagelogistik zu identifizieren sowie Ursache-Wirkungs-Beziehungen zu formulieren. Anschließend werden die vermuteten Zusammenhänge zwischen Komplexitätstreibern und Logistikkennzahlen anhand einer statistischen Kausalanalyse im Rahmen einer Strukturgleichungsmodellierung empirisch überprüft. Darauf aufbauend wird eine Bewertungsmethode zur Operationalisierung von Logistikkomplexität entwickelt und anhand eines Use Cases bei einem deutschen Premium OEM hinsichtlich Praxistauglichkeit und Funktionalität validiert. Die Anwendung der Methodik und die inhaltliche Auseinandersetzung mit dieser ermöglicht es die notwendige Transparenz über Komplexität in der Logistik zu schaffen, diese zu bewerten und dementsprechend Handlungsempfehlungen für ein effektives Komplexitätsmanagement abzuleiten.
The automotive sector has to face various challenges recently and especially logistics as an interdisciplinary field. Globalization and higher market heterogeneity lead to a substantial increase of model variety in the automotive sector. Simultaneously innovation cycles abbreviate due to rising market dynamics. Caused by the necessity to integrate a growing number of models in existing plant structures a considerable increase of complexity is observable within the automobile manufacturer’s plants, especially in logistics. Market based, higher product variety represents a strategic success factor, but the resulting inner variety often has a negative impact on the company’s processes and cost structures. Logistical networks are nowadays determined by a high number of suppliers, variety and dynamic within the network partners. Due to their size and high degree of cross-linking, these networks seem to be chaotic and complex. The ongoing trend of globalization increases this effect. In the coming years, a further increase in complexity is expected in the wake of the growing importance of electromobility, digitalization and networking. However, it is not yet possible to quantify these complexity increases and to make informed statements about their effects on the logistical success. Therefore, transparency is first created on the complexity-driving factors in the assembly logistics, in order to develop an assessment methodology for complexity in logistics. For this purpose, on the basis of a literature research qualitative interviews are conducted, in order to identify the relevant complexity drivers in the assembly logistics as well as to formulate cause-and-effect relationships. Subsequently, the expected connections between complexity drivers and logistic key performance indicators are empirically examined by means of a statistical causal analysis within the framework of a structural equation model. Based on this, an assessment method for the operationalization of logistics complexity is developed and validated with regard to practicality and functionality by a German premium OEM. The application of the methodology and the analysis of the content makes it possible to create the necessary transparency about complexity in the logistics, to evaluate it and to derive recommendations for an effective complexity management accordingly.
The automotive sector has to face various challenges recently and especially logistics as an interdisciplinary field. Globalization and higher market heterogeneity lead to a substantial increase of model variety in the automotive sector. Simultaneously innovation cycles abbreviate due to rising market dynamics. Caused by the necessity to integrate a growing number of models in existing plant structures a considerable increase of complexity is observable within the automobile manufacturer’s plants, especially in logistics. Market based, higher product variety represents a strategic success factor, but the resulting inner variety often has a negative impact on the company’s processes and cost structures. Logistical networks are nowadays determined by a high number of suppliers, variety and dynamic within the network partners. Due to their size and high degree of cross-linking, these networks seem to be chaotic and complex. The ongoing trend of globalization increases this effect. In the coming years, a further increase in complexity is expected in the wake of the growing importance of electromobility, digitalization and networking. However, it is not yet possible to quantify these complexity increases and to make informed statements about their effects on the logistical success. Therefore, transparency is first created on the complexity-driving factors in the assembly logistics, in order to develop an assessment methodology for complexity in logistics. For this purpose, on the basis of a literature research qualitative interviews are conducted, in order to identify the relevant complexity drivers in the assembly logistics as well as to formulate cause-and-effect relationships. Subsequently, the expected connections between complexity drivers and logistic key performance indicators are empirically examined by means of a statistical causal analysis within the framework of a structural equation model. Based on this, an assessment method for the operationalization of logistics complexity is developed and validated with regard to practicality and functionality by a German premium OEM. The application of the methodology and the analysis of the content makes it possible to create the necessary transparency about complexity in the logistics, to evaluate it and to derive recommendations for an effective complexity management accordingly.
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Automobilindustrie, Logistik, Komplexitätsmanagement