The Reality of Shop Floor Control — Approaches to Systems Innovation

Scherer, Eric

doi:10.1007/978-3-642-60313-6_1

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…We use a conceptualization of internal service complexity that is associated with internal service attributes. Hence, we focus on structural aspects of complexity which are caused by the varying number of different elements and their ever-changing interrelationships (Scherer, 1998). In this context, the described structural aspects of complexity are evaluated subjectively by internal customers.…”

Section: Research Background and Literature Review 21 Internal Service Complexity In The Context Of Systems Theorymentioning

confidence: 99%

Determinants of perceived internal service complexity

Braun

Hadwich

2017

EBR

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Purpose This paper aims to explore the determinants of perceived internal service complexity in internal service encounters. In this context, the nature of internal service complexity is considered, to identify its promoting and limiting factors, as well as its non-linear effects on internal service quality. Design/methodology/approach To acquire information on factors influencing internal service complexity, a broad literature review was conducted. Furthermore, to validate and verify these results, structural equation modeling’ was used in the context of a quantitative study with 705 internal customers. Findings The results revealed four promoting and seven limiting complexity determinants at organizational, interdepartmental and internal supplier-related levels. Moreover, the findings showed that an optimal, moderate level of internal service complexity maximizes internal service quality. Research limitations/implications As the findings are restricted to this study, further research should be conducted with regard to different types of companies and internal customers. Furthermore, future research should take variability over time into account. Executing a longitudinal approach to internal service complexity might therefore be appropriate. Practical implications Managers should note that exclusively reducing internal service complexity is insufficient; rather, a hybrid strategy of lowering and controlling is indispensable for an optimization. Based on the identified complexity determinants, a three-step guidance to optimize internal service is proposed. Originality/value Despite examining the construct complexity, previous research has neither analyzed internal service complexity nor studied its determinants. This paper provides an empirical model that analyzes inhibiting and promoting factors of internal service complexity as well as its non-linear effects on internal service quality.

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Section: Research Background and Literature Review 21 Internal Service Complexity In The Context Of Systems Theorymentioning

confidence: 99%

Determinants of perceived internal service complexity

Braun

Hadwich

2017

EBR

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“…Moreover, in case of a simulation model is used for supporting short-term or real-time decisions, it is particularly important to have quick response time. For instance, regarding production control, the closer we are to the short-term plans the more detailed simulation model is needed to accurately support factory control and planning decisions (Scherer 1998). However, detailed models will have lengthy, unacceptable response times.…”

Section: Simulation-based Support Of Production Systemsmentioning

confidence: 99%

Applying model-reconstruction by exploring MES and PLC data for simulation support of production systems

Pfeiffer¹,

Kádár²,

Popovics³

et al. 2012

Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC)

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The paper introduces a discrete-event simulation-based decision supporting system aiming at automatically mirroring the current state of a large-scale material handling system of a production system in a digital model and supporting the analysis of diverse control settings and rules. The discrete-event digital model is built in an automated way and all the data necessary for the model are taken from a manufacturing execution system (MES) and additionally directly from programmable logic controllers (PLC). Main focus is given to present the results of the PLC program code processing method (code mapping) generating a structured dataset, as well as the model-reconstruction method for the simulation software. The easy-of-use support tool is intended to be used both in planning and operation phases of an automotive manufacturing company, thus the capabilities of model reconstruction and simulation are tested on real-world data

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“…Other complexity definitions involve concepts such as entropy, randomness, and information [34][35][36]. Scherer [37] distinguishes between structural complexity, which is caused by the number of elements and their interconnectedness, and dynamic complexity caused by feedback loops and highly dynamic and nonlinear behavior. Moreover, complexity can be understood as interaction between complicatedness and dynamics [38].…”

Section: Proposed Modelmentioning

confidence: 99%

Reducing the structural complexity of growing organizational systems by means of axiomatic designed networks of core competence cells

Matt

2007

Journal of Manufacturing Systems

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The Reality of Shop Floor Control — Approaches to Systems Innovation

Cited by 9 publications

References 7 publications

Determinants of perceived internal service complexity

Determinants of perceived internal service complexity

Applying model-reconstruction by exploring MES and PLC data for simulation support of production systems

Reducing the structural complexity of growing organizational systems by means of axiomatic designed networks of core competence cells

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