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This study explores the interactional effects and fit of internal and external collaboration on supply chain performance based on the fit theory. Data collected from 205 firms located in China was used to test the hypotheses via partial least squares structural equation modelling, polynomial regression and response surface methodology. The results demonstrate that there is an interactive effect, i.e. fit between internal collaboration and external collaboration on supply chain performance – a phenomenon not previously well understood. The results indicate that not all firms implementing internal collaboration and external collaboration can attain the desired goals. Only when the strength and balance of the two are similar, and at a moderate to upper level, can the supply chain performance be achieved the best; and once a certain threshold value of internal collaboration and external collaboration is achieved, further enhancement in internal and external collaboration will cause the decline of supply chain performance. Our study emphasises the importance of balancing internal constraints and external requirements across the whole supply chain, and provides insights into supply chain collaboration by suggesting that internal collaboration and external collaboration must be fit in the pursuit of supply chain performance. [ABSTRACT FROM AUTHOR]

Control charts based on Time Between Events (TBE) have been shown to be effective in high quality processes, where the defects or failures (events) occur at a very low probability. The occurrences of events are usually modeled as a homogeneous Poisson process. The TBE data is likely to follow a skewed distribution, such as the gamma distribution. In order to monitor high quality processes, this study focuses on the development of modified one-sided Exponentially Weighted Moving Average (EWMA) TBE charts. The Monte-Carlo simulation method is used to evaluate the Run Length (RL) properties of the proposed schemes. The results show that the proposed schemes are more sensitive to process shifts than some competitive procedures. Finally, a real data example is provided to illustrate the implementation of the proposed charts. [ABSTRACT FROM AUTHOR]

Assuming that a two-stage serial-parallel processing system is an M/G/m queuing system. Firstly, let sojourn time of the order in one stage is the system state, and the state space equation is used to model this system. Also, the influence of the mean shift of sojourn time on the downstream stage is analyzed. Secondly, the average sojourn time is calculated. And the distribution function of the sojourn time is estimated based on the Laplace-Stieltjes (LS) transformation. Thirdly, a change point control chart is designed based on the sum of squared ranks to monitor back order. Finally, the performance of the change point control chart is evaluated via simulation in terms of average run length, the accuracy of the change point estimation and the out-of-control stage estimation. The results show that the change point control chart can effectively detect the mean shift of the lead time, and it can estimate the change point and its out-of-control stage more accurately. [ABSTRACT FROM AUTHOR]

In this paper, a supply chain system is viewed as a maintainable system, and the economic-statistical design of a likelihood ratio control chart with a maintenance application is considered for this system. The supply chain system is described by a three-state: normal state, warning state and failure state. A likelihood ratio control chart is used to monitor the system given that only categorical observations can be obtained. When the chart signals, a full inspection is performed to determine the actual system state (normal or warning), and preventive maintenance is immediately performed in the warning state. In addition, the supply chain system must be corrected upon failure (i.e. corrective maintenance), and should be maintained in a scheduled time (i.e. planned maintenance). A mathematical model is developed for the joint optimisation of the control chart parameters and planned maintenance time based on renewal theory. An example is presented to illustrate how to determine the optimal design parameters. We also investigate the effect of coefficients and statistical constraints on the decision variables and the expected cost. [ABSTRACT FROM PUBLISHER]

Exponentially weighted moving average (EWMA) type charts are very popular and efficient in monitoring various kind of statistics. Much researches have been done on the EWMA X ¯ chart with known process parameters. But, in practice, the process parameters used to set the control chart limits are often unknown and they need to be estimated from different Phase I samples. Moreover, because the shape of the run length distribution for the EWMA X ¯ chart changes with the mean shift, the median run length (MRL) can serve as a good alternative to evaluate the performance of the EWMA X ¯ chart. In this article, we will investigate the conditional properties of the EWMA X ¯ chart with unknown process parameters based on the MRL metric. In order to investigate the chart's properties, the average MRL (AMRL) and the standard deviation of MRL (SDMRL) will be used together when the process parameters are unknown. To prevent too many lower in-control MRL values, the adjusted control limits of the MRL based EWMA chart are obtained by using a bootstrap type approach and the results show that the adjusted control limits can give a good tradeoff between the in-control and out-of-control MRL performances. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between relationship quality and supply chain quality performance in hotel supply chain, through the mediating effect of supply chain integration. A questionnaire survey is used to collect data relating to the research hypotheses. Structural equation model technique is suited for our research goals, and the SmartPLS software is implemented to test the conceptual model. The results show that relationship quality has a direct and positive impact on supply chain quality performance; but after introducing mediating variable—supply chain integration, relationship quality indirectly affects supply chain quality performance through supply chain integration. This means that a good relationship quality can promote supply chain integration and ultimately improve supply chain quality performance. [ABSTRACT FROM AUTHOR]

In high-quality processes, events related to non-quality rarely occur and the times between these events (TBE) is likely to follow a skewed distribution like the gamma distribution. In order to monitor TBE data, an Adaptive Exponential Weighted Moving Average (AEWMA) control chart is proposed in this paper. This chart is designed to perform well over a range of shifts instead of being only efficient for a particular shift. An extensive performance analysis shows that, for most shifts, the Average Run Length (ARL) of the proposed chart performs better than other already existing control charts. In order to help the quality practitioner, some guidelines for choosing the most effective scheme in practice are provided. Finally, an illustrative example of the proposed scheme is also presented. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

The close relationship between quality and maintenance of manufacturing systems has contributed to the development of integrated models which use the concept of statistical process control (SPC) and maintenance. This article demonstrates the integration of the Shewhart individual-residual (ZX− Ze ) joint control chart and maintenance for two-stage dependent processes by jointly optimizing their policies to minimize the expected total costs associated with quality, maintenance and inspection. To evaluate the effectiveness of the proposed model, two stand-alone models—a maintenance model and an SPC model—are proposed. Then a numerical example is given to illustrate the application of the proposed integrated model. The results show that the integrated model outperforms the two stand-alone models with regard to the expected cost per unit time. Finally, a sensitivity analysis is conducted to develop insights into time parameters and cost parameters that influence the integration efforts. [ABSTRACT FROM AUTHOR]