Evaluation of Complexity Management Systems – Systematical and Maturity-based Approach

Kluth, Andreas; Jäger, Jens; Schatz, Anja; Bauernhansl, Thomas

doi:10.1016/j.procir.2014.01.083

Cited by 22 publications

(17 citation statements)

References 6 publications

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“…The evaluation of these dimensions helps to quantify complexity. Another attempt is to distinguish between internal and external complexity and to describe origins of complexity like variety, heterogeneity, dynamics and non-transparency [15]. These aspects also refere to Ashby's concept of open systems and the requesite variety [16].…”

Section: Resilient Systems In a Complex Environmentmentioning

confidence: 99%

Increased resilience for manufacturing systems in supply networks through data-based turbulence mitigation

Bauer

Böhm

Bauernhansl

et al. 2021

Prod. Eng. Res. Devel.

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In manufacturing systems, a state of high resilience is always desirable. However, internal and external complexity has great influence on these systems. An approach is to increase manufacturing robustness and responsiveness—and thus resilience—by manufacturing control. In order to execute an effective control method, it is necessary to provide sufficient information of high value in terms of data format, quality and time of availability. Nowadays, raw data is available in large quantities. An obstacle to manufacturing control is the short-term handling of events induced by customers and suppliers. These events cause different kinds of turbulence in manufacturing systems. If such turbulences could be evaluated in advance, based on data processing, they could serve as aggregated input data for a control system. This paper presents an approach how to combine turbulence evaluation and the derivation of measures into a learning system for turbulence mitigation. Integrated in manufacturing control, turbulence mitigation increases manufacturing resilience and strengthens the supply network’s resilience.

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Section: Resilient Systems In a Complex Environmentmentioning

confidence: 99%

Increased resilience for manufacturing systems in supply networks through data-based turbulence mitigation

Bauer

Böhm

Bauernhansl

et al. 2021

Prod. Eng. Res. Devel.

Self Cite

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“…However healthcare BI applications focus on supporting information evidence-based decision-making by healthcare service providers and managers (Spruit, Vroon & Batenburg 2014;Simpao et al 2014;Kao et al 2016), while patient decisions tend not to be considered. Kluth et al (2014) classified approaches to complex decision-making, with one approach being 'focusing on individual factors'. This involves dividing the main complex problem into single smaller problems.…”

Section: Complexity In Healthcare Decision Making -A Case For Bi Applmentioning

confidence: 99%

Investigating the Use of Real-Time Data in Nudging Patients" Emergency Department (ED) Attendance Behaviour

2017

Modeling and Simulation of Complexity in Intelligent, Adaptive and Autonomous Systems 2017 (MSCIAAS 2017)

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Decision-making in healthcare is a complex process involving multiple stakeholders. One such stakeholder category is the intended users of the system itselfthe patients. We present a study in which users use real-time hospital operations data to make attendance choices. The work was carried out with the Torbay & South Devon NHS Foundation Trust (TSDFT) and its network of Minor Injury Units (MIUs) and one Emergency Department (ED). The aim of this research was to provide information transparency on ED/MIU waiting times which would allow recipients, including, significantly, patients who are in need of urgent medical attention, to make informed decisions as to the facility that could best serve their needs. This work will contribute towards reducing pressure in ED by redistributing demand for minor ailments among the MIUs, since the MIUs have facilities for the treatment of minor injuries and the ED exists mainly for emergency and life-threating conditions.

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“…Kluth et al (2014) discussed these approaches in detail. They classify the simplest approaches available as "trial and error" or fading out the complexity of the problem.…”

Section: Complexity Management and Decision Makingmentioning

confidence: 99%

“…in Elsawah et al (2015), Carlman et al (2014), and Schiuma et al (2012). Kluth et al (2014) reminded us that, despite all these developments, many companies do not seem to have access to adequate tools for complexity management.…”

Section: Complexity Decision Making: Ageneral Systems Theory (Gst) Pementioning

confidence: 99%

Complexity Decision Making and General Systems Theory: An Educational Perspective

Yurtseven¹,

Buchanan²

2016

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The aim of this paper is to look at some important educational aspects of complexity decision making in a multidisciplinary manner from the perspective of General Systems Theory (GST). First, the major issues involved in complexity management and decision making are summarized as they are viewed in literature, and a review of GST and Systems Thinking is given. The discussion in the paper is developed within the context of GST in general, but concentrated on decision making in the three trends of GST: Operations Research, Cybernetics, and Managerial Cybernetics. Here, the role of Cybernetics in complexity decision making is particularly emphasized. The discussion is then extended to the latest developments in complexity decision making in Science of Complexity and Soft Systems Thinking. The study also includes a framework which is expected to guide instructors who are planning to offer contemporary courses on decision making. The framework provides some clues for assessing the level of complexity for a given situation and selecting the appropriate methodology for solution development.

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Evaluation of Complexity Management Systems – Systematical and Maturity-based Approach

Cited by 22 publications

References 6 publications

Increased resilience for manufacturing systems in supply networks through data-based turbulence mitigation

Increased resilience for manufacturing systems in supply networks through data-based turbulence mitigation

Investigating the Use of Real-Time Data in Nudging Patients" Emergency Department (ED) Attendance Behaviour

Complexity Decision Making and General Systems Theory: An Educational Perspective

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