Vinod K.T., S. Prabagaran and O.A. Joseph
The purpose of this paper is to determine the interaction between dynamic due date assignment methods and scheduling decision rules in a typical dynamic job shop production system…
Abstract
Purpose
The purpose of this paper is to determine the interaction between dynamic due date assignment methods and scheduling decision rules in a typical dynamic job shop production system in which setup times are sequence dependent. Two due date assignment methods and six scheduling rules are considered for detailed investigation. The scheduling rules include two new rules which are modifications of the existing rules. The performance of the job shop system is evaluated using various measures related to flow time and tardiness.
Design/methodology/approach
A discrete-event simulation model is developed to describe the operation of the job shop. The simulation results are subjected to statistical analysis based on the method of analysis of variance. Regression-based analytical models have been developed using the simulation results. Since the due date assignment methods and the scheduling rules are qualitative in nature, they are modeled using dummy variables. The validation of the regression models involves comparing the predictions of the performance measures of the system with the results obtained through simulation.
Findings
The proposed scheduling rules provide better performance for the mean tardiness measure under both the due date assignment methods. The regression models yield a good prediction of the performance of the job shop.
Research limitations/implications
Other methods of due date assignment can also be considered. There is a need for further research to investigate the performance of due date assignment methods and scheduling rules for the experimental conditions that involve system disruptions, namely, breakdowns of machines.
Practical implications
The explicit consideration of sequence-dependent setup time (SDST) certainly enhances the performance of the system. With appropriate combination of due date assignment methods and scheduling rules, better performance of the system can be obtained under different shop floor conditions characterized by setup time and arrival rate of jobs. With reductions in mean flow time and mean tardiness, customers are benefitted in terms of timely delivery promises, thus leading to improved service level of the firm. Reductions in manufacturing lead time can generate numerous other benefits, including lower inventory levels, improved quality, lower costs, and lesser forecasting error.
Originality/value
Two modified scheduling rules for scheduling a dynamic job shop with SDST are proposed. The analysis of the dynamic due date assignment methods in a dynamic job shop with SDST is a significant contribution of the present study. The development of regression-based analytical models for a dynamic job shop operating in an SDST environment is a novelty of the present study.
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Purushothaman Mahesh Babu, Jeff Seadon and Dave Moore
The purpose of this paper is to highlight the prominent cognitive biases that influence Lean practices in organisations that have a multi-cultural work environment which will aid…
Abstract
Purpose
The purpose of this paper is to highlight the prominent cognitive biases that influence Lean practices in organisations that have a multi-cultural work environment which will aid the organisational managers and academics in enhancing the understanding of the human thought process and mitigate them suitably.
Design/methodology/approach
A multiple case study was conducted in organisations that were previously committed to Lean practices and had a multi-cultural work environment. This research was conducted on five companies based on 99 in-depth semi-structured interviews and seven process observations that sought to establish the system-wide cognitive biases present in a multi-cultural Lean environment.
Findings
The novel findings indicate that nine new biases influence Lean implementation and practices in a multi-cultural environment. This study also found strong connectivity between Lean practices and 45 previously identified biases that could affect positively or negatively the lean methodologies and their implementation. Biases were resilient enough that their influence on Lean in multi-cultural workplaces, even with transient populations, did not demonstrate cultural differentiation.
Research limitations/implications
Like any qualitative research, constructivism and narrative analyses are subjected to understanding based on knowledge gained on the subject, and data may have been interpreted differently. Constructivist co-recreation of process scenarios based result limitations is therefore acknowledged. The interactive participation in exploring the knowledge sought after and interaction that could have a probable influence on the participant need to be acknowledged. However, the research design, multiple methods of data collection, generalisation based on data collection and analysis methods limit the effects of these and findings are reliable to a greater extent.
Practical implications
The results can provide an enhanced understanding of biases and insights into a new managerial approach to take remedial steps on biases’ influence on Lean practices that can result in improved productivity and well-being from a business process perspective. Understanding and mitigating the prominent biases can aid Lean manufacturing processes and support decision makers and line managers in improving lean methodologies’ effectiveness and productivity. The biases can be negated and used to implement decisions with ease. The influence of biases and the model could be used as a basis to counter implementation barriers.
Originality/value
To the best of the authors’ knowledge, this is the first study that connects the cognitive perspectives of Lean business processes in a multi-cultural environment to identify the cognitive biases that influence Lean practices in organisations that were previously committed to Lean practices. The novel findings indicate that nine new biases and 45 previously identified biases influence Lean implementation and practices in a multi-cultural environment. The second novelty of this study shows the connection between cognitive biases, Lean implementation and practices in multi-cultural business processes.
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Ibtissem Alguirat, Fatma Lehyani and Alaeddine Zouari
Lean management tools are becoming increasingly applied in different types of organizations around the world. These tools have shown their significant contribution to improving…
Abstract
Purpose
Lean management tools are becoming increasingly applied in different types of organizations around the world. These tools have shown their significant contribution to improving business performance. In this vein, the purpose of this paper is to examine the influence of lean management on both occupational safety and operational excellence in Tunisian companies.
Design/methodology/approach
A survey was conducted among Tunisian companies, and it resulted in the collection of 62 responses that were analyzed using the software SPSS. In addition, a conceptual model linking the practices of the three basic concepts was designed to highlight the hypotheses of the research. Subsequently, factor analysis and structural equation method analysis were conducted to assess the validation of the assumptions.
Findings
The results obtained have shown that lean management has a significant impact on occupational safety. Similarly, occupational safety has a significant impact on operational excellence. However, lean management does not have a significant impact on operational excellence.
Originality/value
This work highlighted the involvement of small and medium-sized enterprise’s managers from emerging economies in the studied concepts’ practices. Likewise, it testified to the impacts of lean management on occupational safety and operational excellence in the Tunisian context.
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Jayaraman Rajagopalan and Sam Solaimani
The practice of lean management (LM) principles has given firms, from a variety of sectors, quantum jumps in productivity and performance. India is at the cusp of a major leap in…
Abstract
Purpose
The practice of lean management (LM) principles has given firms, from a variety of sectors, quantum jumps in productivity and performance. India is at the cusp of a major leap in economic growth, and adoption of LM is a must for ramping up the rate of growth of the GDP speedily, if the government is really intent on achieving its objective of becoming the third or fourth largest economy soon. This paper aims to study the status of implementation of LM in the LM Leaders (LML’s) in the Indian industry, to understand if they are ready to accept the challenges ahead.
Design/methodology/approach
This is an exploratory research study. To study the level of maturity of LM in Indian industry, the authors selected the LM Leaders in the Indian industry (LMLII). By using a well-known survey instrument – the Lean Self -Assessment Tool (LESAT), Version 2.0 – designed and developed by MIT, the authors conducted a longitudinal survey over the period 2013 to 2016, a four-year duration. Surveys were conducted every year.
Findings
Survey results show an improvement in the overall average of “current state” scores between the years 2013 and 2016, indicating that LMLII’s have improved upon their LM adoption during these years. However, there is a striking gap between “where the industry wants to be” and “where it currently is”. This could drive future improvements. Based on the survey results, this paper draws lessons and proposes action points on how to improve the adoption and diffusion of LM principles and practices in the LMLII. Factors which need to be addressed to reinvigorate the practice of LM have been identified and classified as urgent, immediate and short term.
Research limitations/implications
While many “snapshot” studies have been done to study LM in Indian industry, a longitudinal study has not been done. Moreover, previous studies administer questionnaires to one company (case study method) or a group of companies in a sector of the industry. Thus, there was a research gap. A longitudinal study will help us take a holistic approach. In addition, studying LMLII will provide data from the most serious adopters of LM. Both these will add value to the current research on LM in Indian industry. The results will also help the LMLII’s to further improve the practice of LM in a systematic and rigorous way. However, as the study is limited to the LMLII, it would not be possible to apply the knowledge to the Indian industry as a whole. For doing so, one would need a larger, more representative sample.
Practical implications
Using this paper, LMLII’s can develop practices which will improve customer satisfaction and reduce waste in manufacturing. They can ramp up LM intensity to make further quantum jumps in performance.
Social implications
LM, in addition to improving the output/input ratio (producing more for less), also emphasises waste reduction, customer satisfaction and efficient operations. All these three factors are essential for sustainable and happy society.
Originality/value
The work is original. This is the first longitudinal survey of lean practices in the Indian industry to study cross-sectional practices, and the results will propel the Indian industry to intensify the practice of LM.
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Xinquan Cheng, Yuanhong Chen, Pingfan Wang, YanXi Zhou, Xiaojing Wei, Wenjiang Luo and Qingxin Duan
This study aims to introduce an innovative framework for mining tourism reviews that not only excels in sentiment analysis accuracy but also prioritizes user-friendly design for…
Abstract
Purpose
This study aims to introduce an innovative framework for mining tourism reviews that not only excels in sentiment analysis accuracy but also prioritizes user-friendly design for enhanced usability.
Design/methodology/approach
Online reviews of China’s Five Sacred Mountains were analyzed using an integrated methodology. Sentiment analysis was performed using ChatGPT, bidirectional encoder representations from transformers (BERT) and convolutional neural networks, with ChatGPT demonstrating superior performance. Latent Dirichlet allocation extracted key attributes. Models including importance–performance analysis (IPA), asymmetric impact-performance analysis (AIPA) and importance–performance competitor analysis (IPCA) then synthesized findings.
Findings
The results demonstrate that ChatGPT outperforms both machine learning and lexicon-based models in sentiment recognition, exhibiting performance comparable to that of the BERT model. In the case study, integrating sentiment analysis outcomes with IPA reveals deficiencies in both topics and attributes. Moreover, the synergistic combination of IPA, AIPA and IPCA furnishes actionable recommendations for resource management and enables nuanced monitoring of sustainability attributes.
Practical implications
Leveraging this framework in conjunction with the ChatGPT platform for application development can bring practical convenience to the tourism industry. It supports sentiment analysis, topic categorization and opinion mining. Equipped with monitoring capabilities, it provides valuable insights for sustainable improvement, aiding managers in formulating effective marketing strategies.
Originality/value
This research develops a novel multimodel framework integrating various ML/DL techniques and business models in a synergistic way. It provides an innovative and highly accurate yet simple approach to tourism review mining and enhances accessibility of advanced artificial intelligence for sustainable tourism monitoring, addressing limitations of prior methods.
研究目的
本研究旨在引入一种创新的框架, 用于挖掘旅游评论, 不仅在情感分析准确性方面表现出色, 而且还优先考虑用户友好设计, 以提升可用性。
研究方法
本研究使用综合方法分析了中国五岳的在线评论, 使用ChatGPT进行情感分析。LDA提取了关键属性。然后, 包括IPA、AIPA和IPCA在内的模型综合了研究结果。
研究发现
结果表明, ChatGPT在情感识别方面优于机器学习和基于词典的模型, 表现与BERT模型相当。在案例研究中, 将情感分析结果与IPA结合起来揭示了主题和属性的不足。此外, IPA、AIPA和IPCA的协同组合为资源管理提供了可行的建议, 并实现了对可持续属性的细致监控
实践意义
结合ChatGPT平台在应用开发中利用该框架可以为旅游业带来实际便利。它支持情感分析、主题分类和意见挖掘。配备了监控功能, 为可持续改进提供了宝贵的见解, 帮助管理者制定有效的营销策略。
研究创新
本研究开发了一种新颖的多模型框架, 将各种ML/DL技术和商业模型以协同方式整合在一起。它提供了一种创新而高度准确但简单的方法, 用于旅游评论挖掘, 并提升了高级AI的可访问性, 以实现可持续旅游监测。
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The purpose of this paper, an experimental study, is to investigate the optimal machining parameters for turning of nickel-based superalloy Inconel 718 under eco-friendly…
Abstract
Purpose
The purpose of this paper, an experimental study, is to investigate the optimal machining parameters for turning of nickel-based superalloy Inconel 718 under eco-friendly nanofluid minimum quantity lubrication (NMQL) environment to minimize cutting tool flank wear (Vb) and machined surface roughness (Ra).
Design/methodology/approach
The central composite rotatable design approach under response surface methodology (RSM) is adopted to prepare a design of experiments plan for conducting turning experiments.
Findings
The optimum value of input turning parameters: cutting speed (A), feed rate (B) and depth of cut (C) is found as 79.88 m/min, 0.1 mm/rev and 0.2 mm, respectively, with optimal output response parameters: Vb = 138.633 µm and Ra = 0.462 µm at the desirability level of 0.766. Feed rate: B and cutting speed: A2 are the leading model variables affecting Vb, with a percentage contribution rate of 12.06% and 43.69%, respectively, while cutting speed: A and feed rate: B are the significant factors for Ra, having a percentage contribution of 38.25% and 18.03%, respectively. Results of validation experiments confirm that the error between RSM predicted and experimental observed values for Vb and Ra is 3.28% and 3.75%, respectively, which is less than 5%, thus validating that the formed RSM models have a high degree of conformity with the obtained experimental results.
Practical implications
The outcomes of this research can be used as a reference machining database for various metal cutting industries to establish eco-friendly NMQL practices during the turning of superalloy Inconel 718 to enhance cutting tool performance and machined surface integrity.
Originality/value
No study has been communicated till now on the turning of Inconel 718 under NMQL conditions using olive oil blended with multi-walled carbon nanotubes-based nanofluid.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0317/
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Timothy R. Mcilveene, Maggie Davis and Sonia White
From a social cognitive perspective, the current study examines how the relationship between the employee and the organization changes following supervisor motive misattribution…
Abstract
Purpose
From a social cognitive perspective, the current study examines how the relationship between the employee and the organization changes following supervisor motive misattribution of organizational citizenship behavior (OCB).
Design/methodology/approach
The current study utilizes an experimental vignette methodology (EVM), linear regression and Hayes' (2017) Process Version 4 macro in SPSS to examine the relationships between supervisor misattribution of employee OCB, personality and individual differences and future organizational citizenship behavior intentions.
Findings
Results indicate that supervisor misattribution of employee OCB, specifically when the act is attributed to impression management, will reduce the intention to engage in future OCBs. Results also indicate that this negative relationship is enhanced when subordinates are high in openness.
Research limitations/implications
This study extends social exchange theory by demonstrating how the misattribution of motivation to perform OCBs creates a negative social exchange and discourages future organizational citizenship behavior from the employee. The current research demonstrates the importance of supervisors understanding employees' motivations for engaging in (OCB). If an employee engages in OCB based on intrinsic motivation, such as a desire to help others, and their motivation is attributed to external motivation, such as impression management, the employee may feel misunderstood and believe their values and motivations are incorrectly perceived, leading to reduced OCB.
Originality/value
The current research is examined using EVM. By immersing participants in realistic hypothetical scenarios, experimental vignette methodology allows researchers to explore the intricacies of decision-making across unique scenarios, unraveling both the “why” and the “what next” behind decision-making.