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Help Chain (HC) is a problem-solving practice underpinned by lean manufacturing principles and also adopted for health services, which have different complexity characteristics in relation to manufacturing. This study is based on the premise that Social Network Analysis (SNA) might be an effective analytical approach to account for the complexity of HCs in healthcare. Hence, two research questions are addressed: how to model and interpret HCs in health services as a social network and how SNA can either challenge or add to the lean assumptions of HC design. The use of SNA to model HCs was tested in a maternity hospital, where HCs related to five problems were analyzed, concerning the supply of instruments from the centre of sterilised materials to the surgical and obstetrics units. We analyzed the HCs of single problems and then combined the five problem-solving networks to produce a multilayered network that accounted for their interactions. The patterns of social interactions varied according to the problem and three dimensions of actors' performance (i.e. availability, reliability, and agility). SNA unveiled the complexity of HCs and provided guidance for revising the lean assumptions in their design, matching the realities of health services. [ABSTRACT FROM AUTHOR]

Lean Production Systems are enterprise-specific, methodical frameworks for the continuous orientation of all enterprise processes to the customer in order to achieve overall objectives. Due to an increasing complexity of the digital transformation, the design of Lean Production Systems 4.0 is a challenging task for industrial engineering practice. For this, academia and industrial practice were analysed in a combined approach of a systematic literature review and a field study. The systematic literature review of 62 out of 1600 scientific papers shows that especially the tools, processes, and methods in Lean Production Systems are subject to digital transformation. By involving industrial practice in a field study, quantitative and qualitative insights were used to check scientific hypotheses and identify practical requirements by industrial engineers. As a result, 10 guidelines for the design of future Lean Production Systems 4.0 are derived. The practical implications of this paper enhance the evolution of enterprise-specific Lean Production System 4.0 frameworks. [ABSTRACT FROM AUTHOR]

As demonstrated by the existing literature, lean production and management can contribute to the improvement of firm performance. However, there are many companies that struggle to apply its ethos and practices. The key point is that lean production differs from traditional mass production in many ways. Other than that, numerous studies have shown that business management systems must take into account both soft power and hard power. The main purpose of this study is to use the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) tools to find out the soft and hard power factors, rank their importance in identifying the key success factors for the introduction of a lean production system, and assist in making the company's transformation smoother and more successful. The research results verify that a lean production system needs to take into account both soft power and hard power. Lean management in this study concludes the following priorities of critical factors: In hard power (technical dimension): (1) 5S, (2) seven major wastes, (3) solutions to lean production-related issues, (4) storage location management and warehouse management, (5) single minute exchange of die, and (6) total productive maintenance; In soft power (management dimension): (1) teamwork, (2) communication, (3) leadership, (4) culture, (5) initiative, and (6) employee training. The combination of soft power and hard power can improve the success rate of lean management system introduction. [ABSTRACT FROM AUTHOR]

This article examines the impact of integration between Lean Accounting (LA) tools and Just-in-Time (JIT) techniques on Cost Reduction (CR) in a modern sustainable manufacturing environment in Saudi companies, Ethical Standards (ESs) mediate these two variables. A quantitative methodology was used for realizing the study goals and answering study questions. The main tool used for producing the primary data was a fully structured questionnaire with closed-ended questions which was designed and distributed online through a chosen sample of 109 managers and accountants in Saudi industrialization companies. Descriptive and deductive statistics were adopted to deduce the findings. The gathered responses analyzed by SPSS and AMOS and the results pointed out that there is a direct and indirect impact of LA tools and JIT techniques on CR in Saudi industrial companies especially when using ESs. Moreover, these findings could provide decision-makers in Saudi manufacturing companies with the importance of adopting both methods in an integrated way to maximize the profits of these firms. The practical implications of this study are that the implementation of these methods has a positive impact on the promotion of sustainable manufacturing and consequently the achievement of distinct sustainable performance. [ABSTRACT FROM AUTHOR]

This article shows the results of research, analysis and systematization of historical information, scientific works, and regulatory and legal documents in the subject area under consideration in order to synthesize the Concept of scientific management of sustainable development of subjects of modern domestic economy.The results of the work are based on a systematic approach and the scientific and practical experience of the authors. The results of a retro-perspective analysis of management science through the prism of scientific and technological development of Russia in the XX–XXI centuries are presented. The forecast indicators of Russia’s socio-economic development in the field of achieving technological sovereignty are shown. Theoretical and practical significance of the work done consists in the formation and presentation to the scientific and business community of promising conceptual directions of sustainable development of economic entities through the development of adaptive strategy; deployment of industry clusters; introduction and commercialization of innovative technologies; differentiated application of elements of scientific management; formation and development of social capital, taking into account the requirement of protection from cyber threats in the era of industries 4.0 and 5.0.

Complex product and production systems often result in high variability in the production flow, prohibiting the sustainable implementation of lean practices. In this paper the authors introduce a PDCA cycle to analyse and reduce variability in value streams. The value stream is divided into zones, which are then qualified as stable or unstable. Lean practices can be applied in stable zones, unstable zones remain expert-driven. Measures are introduced to reduce variability in unstable zones with the ultimate target, to turn them into stable zones, extending sustainable lean activities in the value stream, step by step. An IT system is developed to acquire, process and visualise the vast amount of data to provide structured information for experts and management for the reduction of variability in production. [ABSTRACT FROM AUTHOR]

In a machining line with a Lean manufacturing environment, such as one used for mass production of automotive components, tool life is determined by a tool counter that is set on the safe side to avoid producing a failed product, so the cutting tools are typically underutilised. On the other hand, cutting parameters optimisation, which has a significant impact on tool life, is not feasible due to the rule that prohibits changing the cutting parameters during mass production to maintain the quality standard. To address both issues, this paper proposes a hybrid monitoring and optimisation process that can be carried out concurrently without interfering with production activities. The monitoring process involves two methods, namely threshold limit-based monitoring and machine learning-based monitoring, for ensuring product quality during the optimisation process. Meanwhile, Bayesian optimisation (BO) is used for the optimisation process due to its capability for autonomous search for the optimum condition of an unknown and expensive objective function. The case study demonstrated BO's ability to find the optimal condition with a small number of samples, while the machine learning method used can monitor tool wear and surface roughness with average errors of 5.5% and 7.7%, respectively. [ABSTRACT FROM AUTHOR]

Purpose: Lean production has been proved to be a cost-effective and efficient means of production that reduces non-valve added activities. Industry 4.0 (I4.0) is a technology-driven platform that allows machines to interact with other systems through artificial intelligence, machine learning, industrial Internet of Things (IoT), etc. that improve the production system with flexibility, quality and customization throughout the whole value chain. New approaches to digitization of lean production have recently been emerged and they are transforming the industry and increasing productivity throughout the value chain. Through this article, an effort has been made to review the research published in this field. Design/methodology/approach: This paper reviews the literature published in various journals, the databases Web of science (WoS), ScienceDirect, Scopus, Emerald etc. were referred with a focus on lean concepts and tools and I4.0 technologies; it has been noticed that the integration of the lean tools with I4.0 technologies is a very effective tool for the industry. Findings: It has been found in the literature published earlier in various journals that lean manufacturing (LM) is commonly acknowledged and considered a best practice to improve the productivity. It is concerned with the tight integration of people into the industrial process through continuous improvement which leads to value addition throughout the whole value chain by eliminating non vale added activities. The findings show that organizations can improve their productivity and flexibility with speed and accuracy by integrating I4.0 technologies with LM, which is foremost need of any industry across the world. Originality/value: This article accentuates the connections between the principles and tools developed under the umbrella of I4.0 and those developed by the LM techniques, with a specific emphasis on how some of the principles and tools of I4.0 improve the implementation of lean principles dependent on the competence levels of the technology. Very few articles have been published in this area, and this paper is an original piece of research covering a review of extant research published in various journals. [ABSTRACT FROM AUTHOR]

In recent years, the principles of lean production have been gradually permeating the field of agricultural production, providing a favorable opportunity for the structural transformation of agricultural practices. To promote the modernization of tobacco agriculture in the Jingdong production area and address the constraints posed by imbalances, lack of coordination, and unsustainability in tobacco leaf development, achieving the core objectives of reducing labor and costs, enhancing quality and efficiency, and ensuring sustainable growth in tobacco leaf production, this study utilizes the construction of high-quality base units by Guangdong Tobacco Corporation as its framework. Through an analysis of the current state of tobacco leaf production in the Jingdong production area, along with practical exploration, this study delineates the construction path of a lean production model for tobacco leaves and evaluates its practical effectiveness. Through practical implementation, a preliminary constructive management mechanism has been established, yielding favorable economic outcomes. The advanced, tailored production technology system for premium tobacco leaf materials in Guangdong Tobacco Corporation’ s Pu’ er base unit has been progressively refined, boosting the income levels of tobacco farmers and the security of base materials. Furthermore, this study offers a further exploration of the considerations for the continuous advancement of the lean production mode for tobacco leaves in Jingdong County. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Selcuk University Social Sciences Institute / Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi is the property of Journal of Selcuk University Social Sciences Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since companies face difficulties and barriers that prevent the implementation of the Lean philosophy because of resistance within the sector to the use of new techniques and tools, more transparent guidelines on the Lean Construction (LC) principles must be established to increase their usefulness and dissemination. This paper proposes a new LC principles deployment method called New PAD. The previous method, called PAD (Preparation, Application, Deployment), was evaluated based on previous exploratory studies and a literature review, which enabled its improvement with the proposal of the New PAD, which was applied and evaluated in a case study of a paver block production process. The main result is the proposal of the New PAD, the validation of which revealed a reduction in production time from 5 hours and 25 minutes to 4 hours and 30 minutes, minimizing flow times. The New PAD proved to be a viable method for implementing Lean Construction principles in various construction activities, and there was a positive evaluation in the case study company. Because of the lack of formalized methods for deploying LC principles, this paper validates the New PAD method, which can fill this gap. [ABSTRACT FROM AUTHOR]

Objective In the context of intelligent manufacturing, the MES (manufacturing execution system), targeting the production line execution layer, is a core component of the information management system. With the rapid promotion of lean production mode in the rail transit vehicle manufacturing industry, problems arising from information silos and information disconnections due to loose control of manufacturing resources and inconvenient collection of production data are exposed alongside the increase in production capacity. Therefore, it is necessary to analyze the application of MES. Method Combining the production organization mode of rail transit vehicle products with workstation-paced lean production and the characteristics of multi-variety, small-batch discrete manufacturing, a MES based on lean production workstation control is constructed using structured process design and mobile internet technology. Result & Conclusion By constructing a three-dimensional relationship of production elements, the structured process design output driving on-site execution is implemented. Through mobile terminal operations, transparent production management is realized. The MES is expanded longitudinally and laterally, and by managing the data of underlying equipment, interconnection of manufacturing data is achieved. The construction of the MES based on lean production workstation control has realized dynamic control of the entire manufacturing process, controllable making production process, grid-based production resources, and transparent production processes.

The literature discusses data science (DS) as a very promising set of techniques and tools to support lean production (LP) practices. DS could aid manufacturing companies in transforming massive real-time data into meaningful knowledge, increasing process transparency and product quality information and supporting improvement activities through data-driven decision-making. However, no attempt has been made in the literature to formalise the links between DS and LP practices. Thus, this study aims to overcome this gap by clarifying the DS techniques and tools that can support LP practices and how to apply them. This study employs a quantitative bibliometric method – specifically, a keyword co-occurrence network analysis – on a set of papers extracted from Scopus. The results obtained allowed the researchers to identify a set of DS techniques and tools that can support LP practices and to develop a model to guide their implementation based on the typical improvement implementation stages of the plan-do-check-act cycle. The model shows how to use DS techniques and tools in LP for: identifying areas for improvement and subsequent implementation (plan); enabling a better knowledge and process management (do); identifying/predicting potential problems and employing statistical process control (check); providing remedial actions and effectively applying process improvement (act). [ABSTRACT FROM AUTHOR]

Despite its potentialities, Lean Automation (LA) has not attracted attention for over two decades. However, due to the new opportunities offered by Industry 4.0 technologies, LA revives expectations and enthusiasm. This paper aims to test empirically the association of LA, in the form of integration of Lean practices and Industry 4.0 technologies, and operational performance. The paper used a rigorous, multi-stage empirical method and data from a set of more than 200 manufacturing firms; one representative from each of the studied companies filled in a survey on Lean practices and Industry 4.0 technology bundles, with productivity, delivery, inventory, quality as performance indicators. The extensive survey results helped in identifying underlying components of LA: one focuses on operational stability and includes practices and technologies supporting efficiency along the supply chain; the other focuses on streamlining the flow, on fastening the process to reach the customer. Moreover, it demonstrates the positive correlation between LA and operational performance. Besides its contribution to the body of knowledge on LA, this research paves the base of improving academics and practitioners understanding of the integration of new technologies with Lean Production systems. [ABSTRACT FROM AUTHOR]

The production management models currently adopted in the construction industry do not adequately describe the relationships between activities and processes. Such models place emphasis on conversions to the detriment of internal logistics of input distribution for various work fronts. In the planning phase, tasks are commonly estimated using the critical path method, program evaluation and review technique, and Gantt charts. However, techniques capable of optimizing physical flows are not widely adopted. In view of this limitation, this study aimed to assess the potential of virtual manufacturing tools in estimating virtual production parameters based on product lifecycle management and real-life data. Data on mortar production and distribution to work locations were collected on site. Then, two simulations were performed. The first simulation was used to construct a virtual model of the mortar distribution process. The second simulation examined the impact of a mortar transportation device on the activity. Subsequently, the efficiency of both simulations was compared. The efficiency of the mortar transportation device was confirmed by the improvements provided by its implementation. Given their limited example of use in civil construction, it will need to be expanded in this study to validate their potential in all activities of the sector. Despite the limitation presented in this work, the virtual manufacturing can be used as one tool for the integrated product development and product lifecycle management to improve the quality, and to reduce the losses during the production lifecycle. [ABSTRACT FROM AUTHOR]

Copyright of Turkish Studies - Economics, Finance, Politics is the property of Electronic Turkish Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: This paper uses dialectical inquiry to explore tensions that arise when adopting Industry 4.0 technologies in a lean production system and their reconciliation mechanisms. Design/methodology/approach: We conducted an in-depth qualitative case study over a 3-year period on an Italian division of an international electrotechnical organisation that produces electrical switches. This organisation successfully adopted Industry 4.0 technologies in a lean production system. The study is based on primary data such as observations and semi-structured interviews, along with secondary data. Findings: We identify four empirically validated dialectic tensions arising across different Industry 4.0 adoption stages due to managers' and workers' contrasting interpretations of technologies. Consequently, we define the related reconciliation mechanisms that allow the effective adoption of various Industry 4.0 technologies to support a lean production system. Originality/value: This is the first empirical investigation of tensions in the adoption of Industry 4.0 technologies in a lean production system. Furthermore, the paper presents four theoretical propositions and a conceptual model describing which tensions arise during the adoption of Industry 4.0 technologies in a lean production system and the reconciliation mechanisms that prevent lean production system deterioration. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to advance the understanding of paradoxes, underlying tensions and potential management strategies when integrating digital technologies into existing lean-based production systems (LPSs), with the aim of achieving synergies and fostering the development of production systems. Design/methodology/approach: This study adopts a collaborative management research (CMR) approach to identify patterns of organisational tensions and paradoxes and explore management strategies to overcome them. The data were collected through interviews and focus group interviews with experts on lean and/or digital technologies from the companies, from documents and from workshops with the in-case researchers. Findings: The findings of this paper provide insights into the salient organisational paradoxes embraced in the integration of digital technologies in LPS by identifying different aspects of the performing, organising, learning and belonging paradoxes. Furthermore, the findings demonstrate the intricacies and relatedness between different paradoxes and their resolutions, and more specifically, how a resolution strategy adopted to manage one paradox might unintentionally generate new tensions. This, in turn, calls for either re-contextualising actions to counteract the drift or the adoption of new resolution strategies. Originality/value: This paper adds perspective to operations management (OM) research through the use of paradox theory, and we (1) provide a fine-grained perspective on why integration sometimes "fails" and label the forces of internal drift as mechanisms of imbalances and (2) provide detailed insights into how different management and resolution strategies are adopted, especially by identifying re-contextualising actions as a key to rebalancing organisational paradoxes in favour of the integration of digital technologies in LPSs. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate whether Industry 4.0 digital technologies can enhance the effects of lean production on social performance. Design/methodology/approach: Survey data collected from China's manufacturing industry are used to test research hypotheses. Findings: The results reveal that the three dimensions of lean production (internal, customer and supplier) have a significant positive effect on social performance and that digital technology advancement (DTA) positively moderates these relationships. DTA adds only a marginal contribution to social performance. Practical implications: This study addresses a new challenging question from manufacturing firms: how to integrate lean, technology and people? The empirical findings provide timely and insightful practical guidance for managers to better understand the role of digital transformation in the traditional lean context. Originality/value: While digitalization is known to complement lean production, this study shows digitalization also complements the effects of lean production on social performance. [ABSTRACT FROM AUTHOR]

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since companies are inclined to implement lean production, researchers have proposed a number of fundamental success factors to facilitate the implementation of this production approach. This study analyzes the critical success factors (CSFs) in lean production extracted from 14 review studies. The interpretive structural modeling approach is utilized to analyze the impact of these critical success factors on one another. The aim is to enhance insights into lean production and facilitate informed decision-making. In this article, a seven-tiered model is presented. According to the conceptual model of success factors in lean production, leadership is positioned at the base of the model and serves as the origin for other factors. It should be regarded as the foremost critical success factor in lean production. When establishing lean production systems, organizations and senior managers should focus on higher levels and critical success factors that underlie the model. Subsequently, nonfuzzy and fuzzy driving and dependence power analyses were conducted that the fuzzy matrix cross-reference multiplication applied to a classification (MICMAC) analysis provides deeper insights into the analysis of driving and dependence power. The fuzzy matrix cross-reference multiplication applied to a classification analysis helped identify some key factors that are highly effective for successfully implementing lean manufacturing. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Business Science (JOBS) / İşletme Bilimi Dergisi (JOBS) is the property of Journal of Business Science / Isletme Bilimi Dergisi (JOBS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, the 5S method was applied in the tool room of a company operating in the aviation field and engaged in machining. Preparations for the 5S study were carried out in June 2020, and after this month, production was started according to the 5S method. Outputs such as defective parts rates due to cutting tools, costs due to tool room, machine waiting due to tool supply and tool preparation time were determined as performance evaluation criteria. Within the scope of preparation, first of all, lean production and 5S trainings were given to company employees. Personnel for the area where 5S will be applied have been determined and necessary planning has been made. Sorting, organizing, cleaning, standardization and discipline steps related to 5S have been successfully implemented, respectively. For the recovery data, the outputs of the first half of 2020 and the last half were compared and evaluated. As a result of this study, 66% improvements were observed in the cost of the tool room, 76% in the downtime rate of the machines due to the tool room, 78% in the scrap rate due to the faulty cutting tool, and 85% in the unnecessary movement load rates in the tool room. As a result of these improvement works, the efficiency of production has increased. With the gray relational analysis, where all outputs are evaluated jointly, it has been revealed that the most productive month in terms of production is November, when production is made by applying the 5S approach. It was observed that the most inefficient month was April, when production was carried out without applying the 5S approach. [ABSTRACT FROM AUTHOR]

The industrial landscape has evolved from mass production to demand-driven systems in a competitive market. Companies face constant change, prompting a need for efficiency and flexibility in operations. The Toyota production system, developed in the 1950s, emphasizes waste reduction and pull-based production. This article explores how the Toyota system is applied in a metallurgical company to reduce waste and improve processes through Kaizen. The general objective of this article is to analyze the pulled production system and its contribution to reducing inventories in the production process in a metallurgical company. This study was operationalized through a qualitative analysis, with the aid of the case study research method within a metallurgical production context. The study participants are a specific sector of the company and data collection involves documentary analysis and secondary data. Data analysis includes content analysis, focusing on reducing lead time and inventories in the production process. Through the implementation of the pull system and the value flow, the production process was optimized, reducing stocks, facilitating quality control, and allowing the rapid identification of anomalies. The development of a future state flow map showed how Toyota Production System tools, such as 5S, visual management and Kanban, can be applied to promote continuous improvement in the manufacturing process. The implementation of the pull system in the sector brought improvements such as production on customer demand, reduced and qualified stocks, ensuring timely deliveries in line with the philosophy of the Toyota Production System, which prioritizes production according to the customer's needs. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the relationship between the implementation of soft lean practices and organizational resilience development in the service sector. Design/methodology/approach: A mixed-methods explanatory design that relied on two sequential and complementary phases was adopted. In the first phase, a quantitative analysis was performed based on data collected from practitioners from service organizations, allowing the identification of the significance of this relationship. In the second phase, the authors used semi-structured interviews with experts to qualitatively assess how this relationship occurs. Findings: Findings indicated that soft lean practices are positively associated with organizational resilience, although the extent of their relationships varies depending on the resilience ability under analysis. Interviews with experts also provided specific details on how such relationships occur, adding insights to the numerical results. Originality/value: This study provides a deeper understanding of the implications of lean management, specifically concerning the support of soft lean practices to develop organizational resilience. Additionally, the identification of this relationship (and how it occurs) allows service organizations to deploy human-related strategies to promote broader adoption of certain soft lean practices. As socio-cultural changes are usually time-consuming, anticipating these organizational resilience needs may result in competitive advantages in the face of disruptive events. [ABSTRACT FROM AUTHOR]

As demonstrated by the existing literature, lean production and management can contribute to the improvement of firm performance. However, there are many companies that struggle to apply its ethos and practices. The key point is that lean production differs from traditional mass production in many ways. Other than that, numerous studies have shown that business management systems must take into account both soft power and hard power. The main purpose of this study is to use the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) tools to find out the soft and hard power factors, rank their importance in identifying the key success factors for the introduction of a lean production system, and assist in making the company’s transformation smoother and more successful. The research results verify that a lean production system needs to take into account both soft power and hard power. Lean management in this study concludes the following priorities of critical factors: In hard power (technical dimension): (1) 5S, (2) seven major wastes, (3) solutions to lean production-related issues, (4) storage location management and warehouse management, (5) single minute exchange of die, and (6) total productive maintenance; In soft power (management dimension): (1) teamwork, (2) communication, (3) leadership, (4) culture, (5) initiative, and (6) employee training. The combination of soft power and hard power can improve the success rate of lean management system introduction.