Identification of CTQs for Complex Products Based on Mutual Information and Improved Gravitational Search Algorithm

The identification of CTQs for complex products is the first step to implement quality control. To improve the efficiency and accuracy of CTQs identification, we propose a novel hybrid approach based on mutual information and improved gravitational search algorithm, which has advantages of filter and wrapper. At first, the information relevance and redundancy are measured by mutual information. Then, the improved gravitational search algorithm is used to search the CTQs. Experimentation is carried out using 2 UCI data sets, and the classification capability of CTQs is tested by SVM and tenfold cross validation. The results show that the presented method is verified to be effective and practically applicable

A value-based network analysis for stakeholder engagement through prefabricated construction life cycle: evidence from China

Over the past decade, prefabricated construction has increasingly gained popularity in addressing environmental concerns while meeting the high construction demand, particularly in developing countries. Accordingly, the concept of stakeholder engagement increasingly garnered attention as it is highly relevant for understanding and explaining the relationships among various stakeholders, like contractors, suppliers, and producers, especially within the fragmented context of prefabrication. To further the field, this study aims to provide a comprehensive qualitative and quantitative analysis for stakeholder engagement in the realm of prefabricated construction via a value-based network. This value-based network analysis is utilized to model multiple relationships between stakeholders as value exchanges, thus enabling to engage them though management with a focus. Specifically, A total of 110 values were identified and analyzed among 12 stakeholders throughout the whole lifecycle via an extensive literature review, interviews, and questionnaires directed at prefabrication practitioners in China. This data collection process garnered 194 valid responses with a 64.7% response rate. The findings show that enhancing stakeholder engagement requires improvements in both the abilities and experiences of developers, and in the collaborative relationships among key stakeholders. These improvements can be achieved by prioritizing the engagement of prefabrication consultants and encouraging the government to issue policies that support developers, producers, and consultants in fostering collaboration. This in-depth network analysis offers practical insights for decision-makers in the management of core stakeholders and value-based relationships, thereby improving stakeholder engagement. Additionally, it expands the current body of knowledge on stakeholder engagement by incorporating the value-based network analysis into the exploration of its stakeholders and relationships

Establishment of a Method for the Identification of Plant-Derived Ingredients in Mānuka Honey

To establish a method to identify the authenticity of manuka honey, this study compared different methods of DNA extraction from mānuka honey pollen, and it developed a DNA extraction method for mānuka honey supernatant and a real-time polymerase chain reaction (real-time PCR) method for the detection of plant-derived ingredients in mānuka honey, including plant internal control, mānuka and kānuka. By analyzing the specificity, sensitivity, detection limit and comparing with the method of the New Zealand Ministry for Primary Industries (MPI), the feasibility, accuracy and equivalence of this method were confirmed. The proposed DNA detection method could replace the MPI method, not only shaking off the dependence on kits, but also making up for the deficiency of identifying mānuka honey pollen only. It has an important application value and scientific significance for the identification of mānuka honey

Joint Optimal Production Planning for Complex Supply Chains Constrained by Carbon Emission Abatement Policies

We focus on the joint production planning of complex supply chains facing stochastic demands and being constrained by carbon emission reduction policies. We pick two typical carbon emission reduction policies to research how emission regulation influences the profit and carbon footprint of a typical supply chain. We use the input-output model to capture the interrelated demand link between an arbitrary pair of two nodes in scenarios without or with carbon emission constraints. We design optimization algorithm to obtain joint optimal production quantities combination for maximizing overall profit under regulatory policies, respectively. Furthermore, numerical studies by featuring exponentially distributed demand compare systemwide performances in various scenarios. We build the “carbon emission elasticity of profit (CEEP)” index as a metric to evaluate the impact of regulatory policies on both chainwide emissions and profit. Our results manifest that by facilitating the mandatory emission cap in proper installation within the network one can balance well effective emission reduction and associated acceptable profit loss. The outcome that CEEP index when implementing Carbon emission tax is elastic implies that the scale of profit loss is greater than that of emission reduction, which shows that this policy is less effective than mandatory cap from industry standpoint at least

Lean Tools, Knowledge Management, and Lean Sustainability: The Moderating Effects of Study Conventions

It is essential for enterprises to develop lean sustainability. In this way, both the learning and understanding of the knowledge of lean tools becomes necessary. In fact, knowledge management plays a key role in the application of lean tools. In this paper, an in-depth exploration is carried out, investigating the mechanism of knowledge management which mediates between lean tools and the lean sustainability of enterprises, as well as the regulatory role of study conventions. Furthermore, a large sample from a questionnaire survey and a model based on structural equations is applied to test our theoretical hypothesis. It can be stated that lean tools display a positive effect on lean sustainability via the mediating role of knowledge management. Additionally, study conventions positively regulate the relationship among lean tools, knowledge management, and lean sustainability

Accelerated Lifetime Data Analysis with a Nonconstant Shape Parameter

Accelerated life test is commonly used for the estimation of high-reliability product. In this paper, we present a simple and efficient approach to estimate the coefficients of acceleration models. Assuming that both scale and shape parameters of Weibull lifetime distribution vary with stress factors, we estimate the parameters of Weibull distribution using maximum likelihood method and reduce the bias of shape parameter estimator. Considering the heteroscedasticity, we compute the estimates of the coefficients of acceleration models through weighted least square method. Additionally, we obtain the confidence interval of low percentile via bootstrapping. We compare the proposed method with other methods using a real lifetime example. Finally, we study the performance of the proposed method by simulation. The simulation results show that our proposed method is effective

EVALUATION SYSTEM FOR LEAN KNOWLEDGE MANAGEMENT ABILITY BASED ON IMPROVED GRAY CORRELATION ANALYSIS

The efficient implementation of lean production requires an accurate understanding of effective lean knowledge management. However, the existing literature lacks research on evaluating lean knowledge management abilities. To accurately measure lean knowledge management levels, this study established an evaluation index system, selected an improved gray correlation analysis method to determine index weights at all levels, and built a comprehensive evaluation model based on lean knowledge acquisition, integration, and application. Descriptive statistics were calculated from a questionnaire on the current situation of knowledge management in a lean implementation process. By comprehensively evaluating the lean knowledge management abilities of the 28 surveyed enterprises, it was determined that knowledge management can promote improvements therein. The research results provide a decision-making basis for enterprises to formulate a lean implementation strategy

Optimal Production Planning for Manufacturing Systems with Instantaneous Stock-Dependent Demand and Imperfect Yields

We consider an EPL model like manufacturing system in presence of production imperfectness and stock-demand dependence simultaneously. During the production process, the system can evolve from in-control state into out-of-control state at any random time, after which the defective items will be generated likely causing quantity loss. Meanwhile, the market demand rate is instantaneously dependent on the timely holding inventory. The manufacturer has to determine his production run length and cycle time by taking into account possible imperfect production, stock-dependent demand, and inventory holding capacity bound. We empolder a model to capture this problem and develop computational algorithm to solve it. We further conduct numerical studies to validate our model and solving method. Sensitivity analyses are reported to show the effect of parameters on the system performance