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The purpose of this paper is to find the optimal power structure that drives green practices in the supply chain and coordinate the costs and benefits of green practices in supply chain under different power structures.

This paper developed a supply chain of one supplier and one manufacturer, in which the supplier and the manufacturer are responsible for the “greening” of products. Then, the game theory modeling method is used to explore the influence of different power structures on green practices in the supply chain. Finally, the authors developed a green cost-sharing contract made by the leader; regarding optimal supply chain profits and green performance, the proposed contracts and the non-coordination situation are compared and tested by a numerical simulation.

The increase of the green practice difficulty of any member in the supply chain will not only reduce the greenness of products at that stage but will also reduce the green investment of the supply chain partner. Becoming a channel leader does not necessarily mean being more profitable than being a follower, and when the green practice difficulty of the leader is less than a certain threshold, ceding dominant power to the follower may benefit both sides. A green cost-sharing contract made by the leader is not necessarily beneficial to all enterprises.

This paper helps to better understand the role of the power relation in realizing the industry's green goals and helps decision-makers to achieve win-win cooperation by adjusting power relations and optimizing green cost-sharing contracts.

The aim of this study is to report the effect of different content of calcium oxide on the process of electromelting magnesia.

The process of molten magnesia was analyzed by finite element simulation and proved by scanning electron microscope.

The results show that with the increase of CaO content, the maximum temperature appreciation increases from 3,616°C To 3,729°C, showing an approximate nonlinear evolution. Low thermal conductivity and low specific heat of CaO result in higher temperature. With the increase of CaO content and temperature, the maximum flow velocity of MgO slag increases from 0.043 to 1.34 mm/s. Under different initial CaO contents, the distribution trend of CaO volume fraction is basically the same, and the CaO volume fraction is evenly distributed between 50 and 225 mm in the furnace.

The influence of different contents of impurity calcium oxide on the process of electromelting magnesia was analyzed and a theoretical system was established.

Self-service technologies (SST) have become more and more pervasive in retail to facilitate autonomous checkout. In this context, customers play an active role and, as such, can be considered as “partial employees.” Partial employees have to perform a wide range of tasks, get rewarded for their work and need to understand the terms of the exchange, all without being subject to a formalized contract. In this research, the authors suggest that partial employees go through a process of organizational socialization that allows them to define the psychological contract they hold with the organization.

In order to investigate the psychological contracts of partial employees, 324 Canadian customers using SST completed an online questionnaire, in which their SST use, psychological contract fulfillment and organizational socialization were measured.

Descriptive analyses highlight that customers as partial employees build a psychological contract with their most frequent retailer, as they perceive not only retailer inducements but also their own contributions. Multiple linear regressions suggest that organizational socialization favors psychological contract fulfillment, but that specific dimensions of organizational socialization are important for employer inducements vs. employee contributions. Moreover, results suggest that the frequency of use of SST as well as the patronage positively predicts psychological contract fulfillment.

This research investigates a specific situation of unconventional employment – that of customers as partial employees with organizations. It contributes to the literature on the psychological contract by broadening its application to new relations and to the literature on customer management by reemphasizing the relevance of the psychological contract in this domain.

In order to minimize the impact of variability on performance of the process, proper understanding of factors interdependencies and their impact on process variability (PV) is required. However, with insufficient/incomplete numerical data, it is not possible to carry out in-depth process analysis. This paper presents a qualitative framework for analyzing factors causing PV and estimating their influence on overall performance of the process.

Fuzzy analytic hierarchy process is used to evaluate the weight of each factor and Bayesian network (BN) is utilized to address the uncertainty and conditional dependencies among factors in each step of the process. The weighted values are fed into the BN for evaluating the impact of each factor to the process. A three axiom-based approach is utilized to partially validate the proposed model.

A case study is conducted on fused filament fabrication (FFF) process in order to demonstrate the applicability of the proposed technique. The result analysis indicates that the proposed model can determine the contribution of each factor and identify the critical factor causing variability in the FFF process. It can also helps in estimating the sigma level, one of the crucial performance measures of a process.

The proposed methodology is aimed to predict the process quality qualitatively due to limited historical quantitative data. Hence, the quality metric is required to be updated with the help of empirical/field data of PV over a period of operational time. Since the proposed method is based on qualitative analysis framework, the subjectivities of judgments in estimating factor weights are involved. Though a fuzzy-based approach has been used in this paper to minimize such subjectivity, however more advanced MCDM techniques can be developed for factor weight evaluation.

As the proposed methodology uses qualitative data for analysis, it is extremely beneficial while dealing with the issue of scarcity of experimental data.

The prediction of the process quality and understanding of difference between product target and achieved reliability before the product fabrication will help the process designer in correcting/modifying the processes in advance hence preventing substantial amount of losses that may happen due to rework and scraping of the products at a later stage.

This qualitative analysis will deal with the issue of data unavailability across the industry. It will help the process designer in identifying root cause of the PV problem and improving performance of the process.

The purpose of this paper is to describe a comprehensive modelling technique that supports the assembly of very complex products that require intensive use of both computerized worker guidance and automation. The modelling enables the planning of this complex process.

The proposed approach utilizes and extends typical product documentation (such as route cards and bill of materials (BOM)) to form hierarchical Petri net in a stepwise process. The suggested framework models the dynamic progress of the assembly process, and can generate route card instructions for manual operations, or ladder diagrams (LDs) for automation.

The model can help the generation of computerized control over route cards for manual assembly operations. For automated processes, the translation algorithm of the model to LD enables its application on currently available equipment (programmable logic controllers (PLCs)).

The proposed framework heavily depends on the BOM data quality. So it is crucial to verify that the BOM data is not ill-defined before applying the proposed framework. Future research could report on the implementation of this model in assembly processes, or suggest another modelling technique.

The model enables the integration of computer control over both manual and automated assembly processes. This enables seamless transition between these two very different operations. This ability carries the promise of reducing the cost of code generation and maintenance, and contributes to the progress towards more flexible automation.

This paper presents a new comprehensive modelling technique that may support planning, simulating, tracing, and controlling the assembly process. The technique for the first time integrates modelling of both manual and automated assembly operation.