Komplexitätsbeherrschung durch hybride Montageplanung

  • Mastering complexity through hybrid assembly planning

Fölling, Carsten; Schuh, Günther (Thesis advisor); Burggräf, Peter (Thesis advisor)

1. Auflage. - Aachen : Apprimus Verlag (2022)
Book, Dissertation / PhD Thesis

In: Ergebnisse aus der Produktionstechnik 27/2022
Page(s)/Article-Nr.: 1 Online-Ressource : Illustrationen, Diagramme

Dissertation, RWTH Aachen University, 2022


The dynamics of today's buyer markets require increasing agility in product development, which results in high complexity and new challenges for assembly planning as a downstream discipline. Existing assembly planning procedures are too rigid and inflexible to react adequately to the requirements of agile product development and the dynamics of the market environment. In particular, the high and increasing complexity in assembly planning leads to the regular non-achievement of planning goals and to insufficient planning results. This problem is aggravated by the increasing frequency of assembly planning projects. Complexity as a critical success factor is not considered explicitly in conventional planning approaches. Accordingly, planning methods are selected without taking complexity into account, which results in the largely untargeted use of methods in assembly planning. Consequently, the specific potentials of planning methods for the mastery of complexity remain unexploited. Hybrid planning procedures combining the specific advantages of plan-driven and agile methods in a targeted manner have great potential for comprehensively mastering complexity and thus for optimizing planning results. To address the aforementioned challenges and to optimize planning results in assembly planning, a model for the systematic determination of dominant planning methods for individual planning scopes is developed in this work. The dominant methods are then combined within hybrid assembly planning procedures for the mastery of planning complexity. To determine dominant planning methods, the planning complexity to be mastered is compared with the potentials of available planning methods. The planning complexity to be mastered is described by the complexity requirements of individual planning scopes. To objectively operationalize and measure complexity requirements, a specific complexity measure is developed, which comprises and mathematically describes the relevant complexity factors. The derivation of complexity potentials is based on the constituent properties of plan-driven and agile planning methods, whose influence on the various dimensions of complexity is examined. The comparison of complexity requirements and complexity potentials is finally executed within the central decision model for determining dominant planning methods. The hybrid assembly planning model developed in this thesis is intended to enable assembly planning in the industrial practice to adequately master planning complexity and to optimize planning results.