Search results

The purpose of this paper is to illustrate the importance of redesigning, reusing, remanufacturing, recovering, recycling and reducing (6R) to sustainable manufacturing and discuss the general procedure to reconfigure robots. Two critical challenges in adopting industrial robots in small and medium-sized enterprise (SMEs) are flexibility and cost, as the number of tasks of the same type can be limited because of the size of an SME. The challenges can be alleviated by 6R. The 6R processes allow a robot to adopt new tasks, increase its utilization rate and reduce unit costs of products.

There is no shortcut to implement sustainable manufacturing. All of the manufacturing resources in a system should be planned optimally to reduce waste and maximize the utilization rates of resources. In this paper, modularization and reconfiguration are emphasized to implement 6R processes in sustainable manufacturing; robots are especially taken into consideration as core functional modules in the system. Modular architecture makes it feasible to integrate robots with low-cost customized modules for various tasks for the high utilization rates. A case study is provided to show the feasibility.

Finding the ways to reuse manufacturing resources could bring significant competitiveness to an SME, in the sense that sophisticated machines and tools, such as robots, can be highly utilized even in a manufacturing environment with low or medium product volumes. The concepts of modularization and 6R processes can be synergized to achieve this goal.

The authors propose the strategy to enhance the utilization rates of core manufacturing resources using modular architecture and 6R practice. The axiomatic design theory can be applied as the theoretical fundamental to guide the 6R processes; however, a universal solution in the implementation is not available. The solutions have to be tailored to specific SMEs, and the solutions should vary with respect to time.

To operate a sustainable manufacturing system, a continuous design effort is required to reconfigure existing resources and enhance their capabilities to fulfill new tasks in the dynamic environment.

The authors focus on the importance of sustainable manufacturing to modern society, and they achieve this goal by reusing robots as system components in different applications.

Sustainable manufacturing has attracted a great deal of attention, although the operable guidance for system implementation is scarce. The presented work has thrown some light in this research area. The 6R concept has been introduced in a modular system to maximize the utilizations of critical manufacturing resources. It is particularly advantageous for SMEs to adopt sophisticated robots cost-effectively.

The set-union knapsack problem is one of the most significant generalizations of the Non-deterministic Polynomial (NP)-hard 0-1 knapsack problem in combinatorial optimization, which has rich application scenarios. Although some researchers performed effective algorithms on normal-sized instances, the authors found these methods deteriorated rapidly as the scale became larger. Therefore, the authors design an efficient yet effective algorithm to solve this large-scale optimization problem, making it applicable to real-world cases under the era of big data.

The authors develop three targeted strategies and adjust them into the adaptive tabu search framework. Specifically, the dynamic item scoring tries to select proper items into the knapsack dynamically to enhance the intensification, while the age-guided perturbation places more emphasis on the diversification of the algorithm. The lightweight neighborhood updating simplifies the neighborhood operators to reduce the algorithm complexity distinctly as well as maintains potential solutions. The authors conduct comparative experiments against currently best solvers to show the performance of the proposed algorithm.

Statistical experiments show that the proposed algorithm can find 18 out of 24 better solutions than other algorithms. For the remaining six instances on which the competitor also achieves the same solutions, ours performs more stably due to its narrow gap between best and mean value. Besides, the convergence time is also verified efficiency against other algorithms.

The authors present the first implementation of heuristic algorithm for solving large-scale set-union knapsack problem and achieve the best results. Also, the authors provide the benchmarks on the website for the first time.

Does client embeddedness lead to improved employee quality of life, such as job satisfaction, affective commitment and employee engagement? If so, is this relationship affected by gender, age, tenure and psychological contract breach (PCB)? The paper aims to discuss these issues.

Regression and ANOVA analysis of a two-wave sample (n=121) of employees working for an aged care provider.

Client embeddedness at Time 1 predicts employee quality of life at Time 2. However, in this sample, this relationship is unaffected by gender, age and length of service. High levels of PCB weakens the relationship between client embeddedness and job satisfaction.

The employee-client relationship directly improves quality of working life. However, it is unclear whether this finding is unique to this organisation, or whether client embeddedness can be cultivated over time or is a characteristic of an employee.

Organisations can substantially benefit from encouraging appropriate client-employee relationships. By adopting HR practices aimed at acquiring and cultivating client embeddedness through recruitment, performance management and training practices, organisations may increase employee quality of working life, and reduce employee turnover.

This paper substantially increases the understanding of client embeddedness by clarifying the direct effects of the client-employee relationship, and by identifying boundary conditions on the effect of client embeddedness. It also points to a distinct approach to recruiting and developing employees in client-facing industries.

The purpose of this paper is to investigate the manners in which the employee and consumer identities interact to shape individuals perceptions of corporate reputations in well-established market economies (Australia and Italy) and transition countries (Bulgaria and Russia).

The study utilises a within-subjects repeated measures design. The data were collected from 892 subjects in Australia, Italy, Bulgaria and Russia. The hypotheses were tested using structural equation modelling.

In established market economies, individuals tend to have very distinct identities as employees or consumers, and make different evaluations of corporate reputations depending on the chosen identity. In contrast, in transition countries, the consumer identity prevails over the employee identity and therefore job seekers tend to “follow” their consumer values in forming value judgements of companies.

The study makes two key contributions to current debates in employer branding and stakeholder management research. First, it contributes to theory and practice in employer branding by developing and testing a model of the interaction between consumer and employee identities in defining individuals’ perceptions of corporate reputations. Second, it contributes to stakeholder theory by investigating consumption and job-search from an integrated perspective rather than as separate and unrelated processes.

The purpose of this study is to present Industry 4.0 technologies for advancing the circular economy (CE) adaption in manufacturing industry’s supply chain (SC) network. To pursue the same, Industry 4.0 technological aspects were recognized as solution measures to overcome the challenges for CE implementation in SC.

A new hierarchical framework containing 13 leading CE challenges and eight promising Industry 4.0 technological aspects had been proposed, representing their mutual relationship. The proposed framework was analysed using a hybrid approach of analytic hierarchy process (AHP) and combinative distance-based assessment (CODAS) under interval-valued intuitionistic fuzzy (IVIF) environment. The IVIF-AHP was used to acquire the priority weights of the CE challenges, whereas the IVIF-CODAS was used to attain the preference order of the proposed technological aspects.

The key findings of the present work indicate that “Information disruptions among the SC members due to multiple channels” and “Manpower inability to handle the toxic materials” are the two most critical challenges hindering the adoption of CE practices in SC. Along with, the results also demonstrate that to overcome these challenges, “Smarter equipment to empower flexibility and mass customization” and “Big data driven decision-making system” are the two most significant Industry 4.0 technological solutions, adoption of which might encourage the organizations to align their operations with CE philosophies.

The sample size of the experts engaged in work was limited; however, big data studies could be conducted in future to capture more insights of the stated topic. In addition to this, to understand the implication of CE on Industry 4.0-based manufacturing, a separate study can be synthesised in future.

The proposed work facilitates a new framework consolidating various perspectives associated with CE implementation into a manufacturing industry considering the scenario of Indian rubber industry. This study enables the decision-makers to recognize the challenging factors for CE implementation into their organizations and up-taking the proposed Industry 4.0 practices as technological measures for improving the organization overall performance.