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The purpose of this paper is to present a decisions support tool that can be applied in initial stages of design, for evaluating the investment feasibility of changeable and reconfigurable manufacturing design concepts, based on future demand predictions and their uncertainties. A quantitative model is proposed, which evaluates the discounted value of capital and operating costs of changeable manufacturing design concepts, based on essential characteristics regarding their type and extent of changeability.

Quantitative empirical modeling is applied, where model conceptualization, validation, and implementation are central elements, using two Danish manufacturing companies as cases.

The applicability of the model is demonstrated in the two case companies, highlighting differences in type, extent, and level of feasible changeability, as a result of differences in product and production characteristics.

Further studies of changeability implementation should be conducted across industrial fields in order to generalize findings.

There is currently limited support for the conceptual design phase of changeable and reconfigurable manufacturing, where critical decisions regarding type, extent, and level of changeability must be made, regardless of high degrees of uncertainty about future demand scenarios.

This paper expands previous research on design for changeability and reconfigurability, by explicitly considering changeability as a capability that can be enabled in various ways for various purposes in different industrial contexts. The proposed model and the case implementations provide important knowledge on the transition toward changeability in industry.

The duration between product design and its successful introduction into the market, also called “Time to Market”, emerges along with cost and quality as one of the crucial factors that decide competition. Considering this trend, several strategies and tools together with examples for a time‐minimising assembly automation are presented.

The purpose of this paper is to transfer the idea of changeability to a concrete technical application.

Based on the definition of changeability on a factory level, a transformation of the five change enablers specified therein for the work station level using the example of an aerodynamic feeding system takes place in this paper.

The observed aerodynamic feeding system can be determined as changeable.

Changeable systems are able to react with low effort to exterior influences, e.g. of the market, and thus represent a considerable competitive advantage.

The new element in this paper is the observation of change enablers on the work station level. This point of view enables the concrete figuration of changeable technical systems.

Detailed study of the causes of stoppages in 40 automatic assembly systems has led to the development of guidelines for improving their availability

To provide a model for precise logistic controlling of one‐piece flow processes and for the description of the interactions between logistic performance measures. The developed method can help manufacturing enterprises to control their production processes and therewith to exploit existing rationalization potentials in their production.

The Institute of Production System and Logistics adapted the logistic operating curve for schedule reliability and the logistic operating curve for mean throughput time to describe the behaviour of one‐piece flow processes. This model‐based method depicts the correlation between the delivery reliability and mean WIP level of single manufacturing systems and enables a goal‐oriented modelling as well as a controlling of single manufacturing processes.

The derivation, calculation, and fields of application of the logistic operating curves for one‐piece flow processes, that give a functional relationship between mean WIP, mean throughput time and schedule reliability, are presented in this paper. Moreover, the paper presents how the logistic performance measures can be adjusted to target values.

This paper offers practical help to manufacturing enterprises confronted with the task of evaluation and optimization of manufacturing processes within the framework of production controlling. Moreover, the developed method enables manufacturing enterprises to identify bottleneck work systems where action can be taken to optimize their schedule situation and thereby improve the delivery reliability of an entire manufacturing department.

The purpose of this paper is to investigate the nonlinear dynamics of the aircraft assembly lines. An approach for modeling and analyzing the production rate of an aircraft assembly line is introduced using the chaos theory.

First, two key system variables including reliability and learning ability are considered to control the dynamics model. The discrete-time dynamics equation of the production rate is established as a function of the reliability and the learning rate. Then an improved Gauss-learning curve is proposed and applied to aircraft assembling condition. Finally, the bifurcation diagrams and the maximal Lyapunov exponents are used and applied to the experimental study to analyze the dynamic behavior under different combinations of parameters.

On the basis of the experimental study, it is shown that chaotic behavior really exists in the aircraft assembly lines. The reliability and the Gauss-learning curve can nonlinearly affect the production rate.

This paper applied nonlinear dynamics and chaotic theory to the production analyses of the aircraft assembly lines for the first time. The proposed model has been successfully applied to a practical case, and the result justifies its advantage as well as feasibility to both theory and engineering application.

The purpose of this paper is to explore theoretical and practical challenges to achieve reconfigurable production system designs.

The empirical material of this paper includes a multiple-case study with an embedded design (Yin) including four cases, where each case represents a production system design project. The consideration of reconfigurability and its characteristics in the production system design projects was studied. To enhance validity, two real-time studies were combined with two retrospective studies (Leonard-Barton).

For more than a decade foresight reports have pointed out the need for responsiveness to change through reconfigurability in production system design. In order to achieve reconfigurable production systems, three challenges were identified: to use a structured design methodology, to gain knowledge in reconfigurability and its characteristics, and to include the reconfigurability knowledge in a structured design methodology. Still there is no comprehensive support available for reconfigurability in the production system design process.

Limitations are mostly related to the chosen methodology approach, and additional empirical studies to establish generic results are required.

By combining knowledge from the production system design field with the reconfigurable manufacturing system field a potential of meeting identified challenges is pointed out.

This paper adds to current knowledge by pointing out three main challenges to achieving reconfigurable production systems. The paper also contributes with ideas on how to respond to these challenges.

During design of reconfigurable manufacturing systems, manufacturing companies need to select and implement the right enablers of reconfigurability in accordance with the specific requirements being present in the manufacturing setting. Therefore, the purpose of this paper is to investigate enablers of reconfigurability in terms of their importance in industry, current level of implementation in industry, and significant differences in their implementation and criticality across different manufacturing settings.

A questionnaire survey is conducted, in order to provide generalizable empirical evidence across various industries and manufacturing types.

The findings indicate that the level of implementation of the reconfigurability enablers is rudimentary, while their criticality is perceived higher than the current level of implementation. Moreover, significant differences regarding implementation and criticality of mobility, scalability, and convertibility were found for companies with varying degrees of manual work, make-to-stock production, and varying production volume, industry type and organization size.

Main limitations of the research cover the relatively small sample size and non-random sampling method applied, primarily limited to one country, which could be increased to further extent the findings reported in this paper.

The findings indicate that the importance and implementation of reconfigurability enablers is contingent on the manufacturing setting. Thus, the research presented in this paper provides valuable knowledge in regard to aiding a paradigm shift in industry and help companies design manufacturing systems with the right reconfigurability enablers.

This paper expands research on manufacturing system design for changeability and reconfigurability, by explicitly considering these as capabilities that can be enabled in various ways for various purposes in different manufacturing contexts.

The organization of production processes is becoming increasingly complex. Begins with some observations of non‐linear dynamic effects and uncontrolled self‐organization in production, which back this statement. This leads to the demand for organization forms in which distributed decision making plays a crucial role. Against this background, however, a new conception of planning and control is necessary. The main question is how an overall corporate objective can be achieved, while the sub‐systems pursue their individual objectives and can only be controlled in a limited manner. The application of recent research results from systems theory can help in understanding the problem and concepts like interventionist and experimental planning are powerful expedients to describe the remaining rules of planning and control specialists. With regard to the decision‐making processes on the shopfloor, suggests a reliance on the laws of the market, which therefore have to be transferred to production systems.