Gu Qiaolun, Ji Jianhua and Gao Tiegang
The purpose of this paper is to present the collecting price decisions of used products in reverse supply chains based on the following cases: manufacturer for collecting and…
Abstract
Purpose
The purpose of this paper is to present the collecting price decisions of used products in reverse supply chains based on the following cases: manufacturer for collecting and processing, third party for collecting and manufacturer for processing, retailer for collecting and manufacture for processing, and third party for collecting and processing.
Design/methodology/approach
The paper considers a recycling channel whereby a manufacturer collects and processes the used products or delegates collecting (or processing) to the retailer or a third party; characterizes the steps of processing a returned used product; gives a collection function of used products which is an increasing function of the collecting price, since the quantity of returned used products is affected by the end customer's willingness and the end customer's willingness is affected by the collecting price. The optimal results were obtained by game theory.
Findings
By investigating the pricing decisions for different cases, the manufacturer prefers to collect the used products rather than delegate to others if manufacturer for processing, and a third party joining the reverse supply chains hopes to collaborate more deeply, not only collecting but also processing the used products.
Research limitations/implications
The main implication is that the reusing ratio of the returned used products and the remanufacturing ratio of the key parts have impacts on the optimal pricing decisions of reverse supply chains.
Practical implications
The paper describes a very useful method for managers to make collecting price decisions for reverse supply chains.
Originality/value
The paper provides the optimal results of collecting price decisions. The paper contributes to the reverse supply chains researches and managers who are responsible for the reverse supply chains.
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Jiaqing Shen, Xu Bai, Xiaoguang Tu and Jianhua Liu
Unmanned aerial vehicles (UAVs), known for their exceptional flexibility and maneuverability, have become an integral part of mobile edge computing systems in edge networks. This…
Abstract
Purpose
Unmanned aerial vehicles (UAVs), known for their exceptional flexibility and maneuverability, have become an integral part of mobile edge computing systems in edge networks. This paper aims to minimize system costs within a communication cycle. To this end, this paper has developed a model for task offloading in UAV-assisted edge networks under dynamic channel conditions. This study seeks to efficiently execute task offloading while satisfying UAV energy constraints, and validates the effectiveness of the proposed method through performance comparisons with other similar algorithms.
Design/methodology/approach
To address this issue, this paper proposes a task offloading and trajectory optimization algorithm using deep deterministic policy gradient, which jointly optimizes Internet of Things (IoT) device scheduling, power distribution, task offloading and UAV flight trajectory to minimize system costs.
Findings
The analysis of simulation results indicates that this algorithm achieves lower redundancy compared to others, along with reductions in task size by 22.8%, flight time by 34.5%, number of IoT devices by 11.8%, UAV computing power by 25.35% and the required cycle for per-bit tasks by 33.6%.
Originality/value
A multi-objective optimization problem is established under dynamic channel conditions, and the effectiveness of this approach is validated.
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Weijie Zhou, Jianhua Zhu and Ce Zhang
This paper aims to introduce corporate social responsibility into the green supply chain and analyse the impact of different decision makers’ decision-making schemes on carbon…
Abstract
Purpose
This paper aims to introduce corporate social responsibility into the green supply chain and analyse the impact of different decision makers’ decision-making schemes on carbon emission reduction in the supply chain.
Design/methodology/approach
This study uses a two-stage low-carbon supply chain composed of a manufacturer and retailer as the research object. It uses the Stackelberg game model to analyse optimal carbon emission reduction and its influence under different decision-making modes.
Findings
Increased consumer green preferences and trust can improve the manufacturing enterprises’ carbon emission reduction rate. The carbon emission reduction rate decreases with increased green innovation costs. When green technology innovation costs remain constant, the greater the market capacity, the higher the carbon emission reduction rate. Market capacity has the most significant impact on the optimal carbon emission reduction rate without considering social responsibility decisions and has the least impact on the optimal carbon emission reduction rate while fully considering the social responsibility decision. To achieve decarbonisation production, the market capacity must be small, and when green innovation costs are high, it is the optimal choice without considering social responsibility. To achieve a higher level of carbon emission reduction, when the market capacity is low and the research and development cost is high or when the market capacity is large, it is the optimal choice.
Originality/value
The results provide scientific policy decisions and management significance for governments and enterprises in low-carbon subsidies and supply chain management. The findings also provide a basis for future theoretical research and enterprise practice.
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Jianhua Xiao, Liu Cao and Lufang Zhang
The purpose of this paper is to compare the contribution of organizational intelligence quotient (OIQ) and organizational emotional quotient (OEQ) for intelligent organizations.
Abstract
Purpose
The purpose of this paper is to compare the contribution of organizational intelligence quotient (OIQ) and organizational emotional quotient (OEQ) for intelligent organizations.
Design/methodology/approach
This paper develops a framework of OIQ and OEQ, based on the structure of intellectual capital (intellectual capital). Then, a specific questionnaire is designed and sent to ten national research institutes in China. Data from nine of them are analyzed as case study samples.
Findings
Data show that intelligent organizations are related with high OIQ as well as high OEQ. In the case of average-intelligent organizations, even if around high-IQ employees, “collective stupidity” caused by the failure of synergy of structural capital is the major gap to be a smart organization, just like a football team grouped by brilliant players always loses due to the dearth of coordination. OEQ, or the synergy between structural capital and human capital, is the critical point to avoid collective stupidity for organizations with intelligent employees.
Research limitations/implications
Research results are based on case study in a particular country. Measurement tools for OIQ and OEQ are in bound of the IC concept.
Practical implications
The paper helps organizations to find out the critical problems causing collective stupidity in a changing environment.
Originality/value
Analogic to human beings’ intelligence, this paper develops a frame of OIQ and OEQ, and compares their contribution to intelligent organization building in a changing environment.
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Jianhua Zhu, Luxin Wan, Huijuan Zhao, Longzhen Yu and Siyu Xiao
The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development…
Abstract
Purpose
The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development of intelligent manufacturing in China. However, many enterprises blindly invest in TIOII, which affects their normal production and operation.
Design/methodology/approach
This study establishes an efficiency evaluation model for TIOII. In this paper, entropy analytic hierarchy process (AHP) constraint cone and cross-efficiency are added based on traditional data envelopment analysis (DEA) model, and entropy AHP–cross-efficiency DEA model is proposed. Then, statistical analysis is carried out on the integration efficiency of enterprises in Guangzhou using cross-sectional data, and the traditional DEA model and entropy AHP–cross-efficiency DEA model are used to analyze the integration efficiency of enterprises.
Findings
The data show that the efficiency of enterprise integration is at a medium level in Guangzhou. The efficiency of enterprise integration has no significant relationship with enterprise size and production type but has a low negative correlation with the development level of enterprise integration. In addition, the improved DEA model can better reflect the real integration efficiency of enterprises and obtain complete ranking results.
Originality/value
By adding the entropy AHP constraint cone and cross-efficiency, the traditional DEA model is improved. The improved DEA model can better reflect the real efficiency of TIOII and obtain complete ranking results.
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Jianhua Su, Hong Qiao, Zhicai Ou and Yuren Zhang
The purpose of this paper is to give a novel sensor‐less manipulation strategy for the high‐precision assembly of an eccentric peg into a hole.
Abstract
Purpose
The purpose of this paper is to give a novel sensor‐less manipulation strategy for the high‐precision assembly of an eccentric peg into a hole.
Design/methodology/approach
Based on the authors' previous work on the attractive region, this paper proposes the sensorless eccentric peg‐hole insertion strategy. The analysis is based on the visible strategic behaviors by decomposing the high‐dimensional configuration space of the eccentric peg‐hole into two low dimensional configuration subspaces. Then, the robotic manipulations can be designed in the configuration subspaces. Finally, a typical industry application, fitting an eccentric crankshaft into a bearing hole of the automotive air‐conditioners, is used to validate the presented strategy.
Findings
The attractive region constructed in the configuration space has been applied to guide the robotic manipulations, such as, the locating and the insertion.
Practical implications
The designed robotic assembly system without using force sensor or flexible wrist has an advantage in terms of expense and durability for the automotive air‐conditioners manufacturing industry.
Originality/value
Most previous work on sensorless manipulation strategy has concentrated on inserting a symmetric peg into a hole. However, for the assembly of an eccentric peg into a hole, the robotic manipulations should be explored in a high‐dimensional configuration space as the six‐DOFs of the eccentric peg. In this paper, the decomposition method of the high‐dimensional configuration space would make the system analysis visible; then, the assembly strategy can be easily designed in the two subspaces.
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Hangjun Zhang, Jinhui Fang, Jianhua Wei, Huan Yu and Qiang Zhang
This paper aims to present an adaptive sliding mode control (ASMC) for tunnel boring machine cutterhead telescopic system with uncertainties to achieve a high-precision trajectory…
Abstract
Purpose
This paper aims to present an adaptive sliding mode control (ASMC) for tunnel boring machine cutterhead telescopic system with uncertainties to achieve a high-precision trajectory in complex strata. This method could be applied to solve the problems caused by linear and nonlinear model uncertainties.
Design/methodology/approach
First, an integral-type sliding surface is defined to reduce the static tracking error. Second, a projection type adaptation law is designed to approximate the linear and nonlinear redefined parameters of the electrohydraulic system. Third, a nonlinear robust term with a continuous approximation function is presented for handling load force uncertainty and reducing sliding mode chattering. Moreover, Lyapunov theory is applied to guarantee the stability of the closed-loop system. Finally, the effectiveness of the proposed controller is proved by comparative experiments on a scaled test rig.
Findings
The linear and nonlinear model uncertainties lead to large variations in the dynamics of the mechanism and the tracking error. To achieve precise position tracking, an adaptation law was integrated into the sliding mode control which compensated for model uncertainties. Besides, the inherent sliding mode chattering was reduced by a continuous approximation function, while load force uncertainty was solved by a nonlinear robust feedback. Therefore, a novel ASMC for tunnel boring machine cutterhead telescopic system with uncertainties can improve its tracking precision and reduce the sliding mode chattering.
Originality/value
To the best of the authors’ knowledge, the ASMC is proposed for the first time to control the tunnel boring machine cutterhead telescopic system with uncertainties. The presented control is effective not only in control accuracy but also in parameter uncertainty.
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Jianhua Ren, Junjie Zhao and Xinyi Liu
With the twin screw extruder being widely used, there are a lot of parameters considered in the method, and the extruder’s volume is an important parameter of twin screw extruders…
Abstract
Purpose
With the twin screw extruder being widely used, there are a lot of parameters considered in the method, and the extruder’s volume is an important parameter of twin screw extruders among them. In this paper, some of the extruder parameters such as the impacting extruder volume are introduced, and the mathematical relationship in these parameters is interpreted. The minimum power consumption is the goal of the authors’ structural design.
Design/methodology/approach
This paper further applies genetic algorithm, a kind of intelligent optimization methods, to obtain the most optimized design dimension, and power consumption function related to unit output of extruder is used as the optimizing target. Meanwhile, this paper takes channel depth of feeding section, channel depth of extrusion section affecting the energy consumption, the width of flight top and helix angle as design variables.
Findings
By using genetic algorithm, the optimal structure size is obtained, and the power consumption is minimum.
Originality/value
With the use of optimizing the structure, the power of consumption is reduced. This method has important economic significance and important social significance on energy saving.
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Bei Liu and Jianhua Cai
This paper aims to solve the problem that multiscale dispersion entropy (MDE) is prone to information loss in the process of coarse-grain, which makes it difficult to extract…
Abstract
Purpose
This paper aims to solve the problem that multiscale dispersion entropy (MDE) is prone to information loss in the process of coarse-grain, which makes it difficult to extract bearing fault information comprehensively.
Design/methodology/approach
A new fault diagnosis method of rolling bearing using refined composite multiscale peak-to-peak normalized dispersion entropy (RCMPNDE) and sparrow search algorithm optimized probabilistic neural network (SSA-PNN) is proposed. First, coarse-graining employs the peak-to-peak value calculation instead of the segmented mean calculation in the RCMDE algorithm, which can overcome the shortcomings of traditional coarse-graining and highlight the fault characteristics. Then, the influence of the selection of different parameters is reduced through the normalization operation, and the RCMPNDE is formed. Finally, the extracted feature parameters are combined with SSA-PNN for diagnosis recognition to construct the RCMPNDE-SSA-PNN fault diagnosis method.
Findings
The proposed RCMPNDE-SSA-PNN fault diagnosis method is tested on actual data sets and its outcomes have been compared to those generated by methods built upon MDE, RCMDE and PNN. The comparison results showed that the proposed method can extract the fault feature information of rolling bearings more accurately and improve the accuracy of fault classification. The recognition accuracy reached 98.5% under the conditions of this experiment.
Originality/value
The RCMPNDE-SSA-PNN method can obtain more accurate fault diagnosis accuracy and provide a new reliable diagnosis method for rolling bearing fault diagnosis.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0332/
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Muhammad Usman Shehzad, Jianhua Zhang, Mir Dost, Muhammad Shakil Ahmad and Sajjad Alam
Given the critical importance of green innovation (GI) for organizations in developing economies, this study aims to examine the interrelationship between knowledge management…
Abstract
Purpose
Given the critical importance of green innovation (GI) for organizations in developing economies, this study aims to examine the interrelationship between knowledge management (KM) enablers, KM processes and GI. The research also indicates that certain combinations of KM enabler dimensions and KM processes can lead to better GI.
Design/methodology/approach
The study sample consists of 328 participants from Pakistan's medium- and large-sized manufacturing enterprises. Smart PLS 3.2.9 is used to verify the relationships. Moreover, the fuzzy set qualitative comparative analysis (fsQCA) investigates configurational paths for improving GI.
Findings
The results demonstrate that KM enablers significantly affect two aspects of GI – green product and process innovation – and KM processes. Moreover, KM processes significantly enhance two aspects of GI. The fsQCA findings indicate multiple combinations of KM enablers and KM processes dimensions that result in better GI.
Research limitations/implications
To better understand the critical role of knowledge resources, future studies should explore the potential mediating mechanisms of KM processes or the moderating effects of strategic organizational factors in the relationship between KM enablers and GI.
Practical implications
The study offers valuable insight and a unique approach for policymakers and executives of corporations in developing countries to enhance their organizations' GI capacity through KM enablers and KM processes.
Originality/value
This research contributes to bridging research gaps in the literature and advances insights into the interrelationship among KM enablers, KM processes and GI. In addition, the study offers methodological significance by combining direct and configurational techniques to address two distinct facets of GI.