Partner selection in sustainable supply chains: a fuzzy ensemble learning model

With the increasing demands on businesses to operate more sustainably, firms must ensure that the performance of their whole supply chain in sustainability is optimized. As partner selection is critical to supply chain management, focal firms now need to select supply chain partners that can offer a high level of competence in sustainability. This paper proposes a novel multi-partner classification model for the partner qualification and classification process, combining ensemble learning technology and fuzzy set theory. The proposed model enables potential partners to be classified into one of four categories (strategic partner, preference partner, leverage partner and routine partner), thereby allowing distinctive partner management strategies to be applied for each category. The model provides for the simultaneous optimization of both efficiency in its use of multi-partner and multi-dimension evaluation data, and effectiveness in dealing with the vagueness and uncertainty of linguistic commentary data. Compared to more conventional methods, the proposed model has the advantage of offering a simple classification and a stable prediction performance. The practical efficacy of the model is illustrated by an application in a listed electronic equipment and instrument manufacturing company based in southeastern China

Analysis and Management of the Price Volatility in the Construction Industry

The problem of price volatility as it pertains to material and labor is a major source of risk and financial distress for all the participants in the construction industry. The overarching goal of this dissertation is to address this problem from both viewpoints of risk analysis and risk management. This dissertation offers three independent papers addressing this goal. In the first paper using the Engineering News Record Construction Cost Index (ENR CCI), a predictive model is developed. The model uses General Autoregressive Conditional Heteroscedastic (GARCH) approach which facilitates both forecasting of the future values of the CCI, and capturing and quantifying its volatilities as a separate measure of risk through the passage of time. GARCH (1,1) was recognized as the best model. The maximum volatility was observed in October 2008 and results showed persistent volatility of the CCI in the case of external economic shocks. In the second paper using the same cost index (ENR CCI), the methodology of the first paper is integrated with Value at Risk concept to cautiously estimate the escalation factor in both short and long-term construction projects for avoiding cost overrun due to price volatilities and inflation. Proposed methodology was also applied to two construction projects in which the estimated escalation factors revealed satisfactory performances in terms of accuracy and reliability. Finally, the third paper addresses the price volatility from the view of risk management. It entails two objectives of identifying and ranking of potential management strategies. The former is achieved via in-depth literature review and questionnaire interviews with industry experts. The latter is done using Analytic Hierarchy Process (AHP). Quantitative risk management methods, alike those offered in foregoing papers are considered as one of the candidates in dealing with the price volatility risk. Cost, risk allocation and duration were perceived as the most significant criteria (project indicators) in construction projects. Also, Integrated Project Delivery (IPD) with respect to project duration; quantitative risk management methods with respect to the cost; and Price Adjustment Clauses (PAC) with respect to the risk allocation, were recognized as the top strategies to manage the risk of price volatilities

The exploration of a category theory-based virtual Geometrical product specification system for design and manufacturing

In order to ensure quality of products and to facilitate global outsourcing, almost all the so-called “world-class” manufacturing companies nowadays are applying various tools and methods to maintain the consistency of a product’s characteristics throughout its manufacturing life cycle. Among these, for ensuring the consistency of the geometric characteristics, a tolerancing language − the Geometrical Product Specification (GPS) has been widely adopted to precisely transform the functional requirements from customers into manufactured workpieces expressed as tolerance notes in technical drawings. Although commonly acknowledged by industrial users as one of the most successful efforts in integrating existing manufacturing life-cycle standards, current GPS implementations and software packages suffer from several drawbacks in their practical use, possibly the most significant, the difficulties in inferring the data for the “best” solutions. The problem stemmed from the foundation of data structures and knowledge-based system design. This indicates that there need to be a “new” software system to facilitate GPS applications. The presented thesis introduced an innovative knowledge-based system − the VirtualGPS − that provides an integrated GPS knowledge platform based on a stable and efficient database structure with knowledge generation and accessing facilities. The system focuses on solving the intrinsic product design and production problems by acting as a virtual domain expert through translating GPS standards and rules into the forms of computerized expert advices and warnings. Furthermore, this system can be used as a training tool for young and new engineers to understand the huge amount of GPS standards in a relative “quicker” manner. The thesis started with a detailed discussion of the proposed categorical modelling mechanism, which has been devised based on the Category Theory. It provided a unified mechanism for knowledge acquisition and representation, knowledge-based system design, and database schema modelling. As a core part for assessing this knowledge-based system, the implementation of the categorical Database Management System (DBMS) is also presented in this thesis. The focus then moved on to demonstrate the design and implementation of the proposed VirtualGPS system. The tests and evaluations of this system were illustrated in Chapter 6. Finally, the thesis summarized the contributions to knowledge in Chapter 7. After thoroughly reviewing the project, the conclusions reached construe that the III entire VirtualGPS system was designed and implemented to conform to Category Theory and object-oriented programming rules. The initial tests and performance analyses show that the system facilitates the geometric product manufacturing operations and benefits the manufacturers and engineers alike from function designs, to a manufacturing and verification