Increasing Energy Efficiency Based on the Kaizen Approach

Androniceanu, Armenia; Enache, I.; Valter, Elena-Narcisa; Raduica, Florin-Felix

doi:10.3390/en16041930

Cited by 13 publications

(16 citation statements)

References 73 publications

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“…For this reason, wastage-Overproduction-does not tend to occur in a company. Inventory represents excess stock of materials, semi-finished goods, and components, including finished goods [2,43,51]. In the company under study, there were no warehouses with material.…”

Section: Visual Workplace Xmentioning

confidence: 99%

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Implementation of Quality Tools in Mechanical Engineering Piece Production

Markulik,

Šolc,

Fiľo

2024

Applied Sciences

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The world is undergoing dynamic changes. For businesses, it brings positives, but also negatives. The positive is the global market for business. The downside of the global market is the increasing competitive pressure. Large enterprises with serial production who are setting production for a longer period ahead are not so noticeable. Small companies are the most vulnerable. There are various tools or overall approaches to business management that allow them to increase work efficiency or production productivity or eliminate waste. In recent years, one can see an increase in the popularity of Lean or Six Sigma. Their contribution to businesses cannot be disputed. Most of the tools and approaches to support business management are oriented or based on the conditions of serial production. Small businesses with piece production are at a disadvantage here. It was this fact that motivated us to focus on piece production and to find space for the implementation of supporting tools that could be helpful. Our research has shown that there are tools that can be applied in the conditions of piece production. The application of the identified tools proved that the results achieved in reducing production times or increasing productivity are unmistakable.

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Section: Visual Workplace Xmentioning

confidence: 99%

“…Motion represents unnecessary staff movements. The company is a logically arranged workplace, including the necessary materials, to minimize the movement of workers during work activities [42,51]. All material brought into the plant is deposited directly into the production area where it is processed.…”

Section: Visual Workplace Xmentioning

confidence: 99%

Implementation of Quality Tools in Mechanical Engineering Piece Production

Markulik,

Šolc,

Fiľo

2024

Applied Sciences

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“…Krzywda et al [20] discuss the decarbonization process of Poland, which has a tradition of using coal as a main energy resource. Androniceanu et al [21] study how to increase energy efficiency with the Kaizen approach.…”

Section: The Stage Of Knowledge In the Fieldmentioning

confidence: 99%

A Comprehensive Analysis of Renewable Energy Based on Integrating Economic Cybernetics and the Autoregressive Distributed Lag Model—The Case of Romania

et al. 2023

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Renewable energy represents a crucial resource in the efforts to combat climate change and reduce dependence on fossil fuels. In the past few decades, Romania has lessened its environmental footprint and played an important role in actions against climate change. In this research, the energy sector in Romania is analyzed from a holistic perspective as a complex adaptive system by using econometric tools. The purpose of the research is to analyze the Romanian energy sector as a cybernetic system and to study the long-run and the short-run causal impact of greenhouse gas emissions (GHG) and renewable energy (RE) on real GDP per capita. The causality among GHG, foreign direct investment (FDI), RE, and real GDP is checked by means of the autoregressive distributed lag model (ARDL). The time series are extracted from Eurostat and OECD databases and cover the period 2000-2021. The results reveal that (i) the variables are cointegrated according to the ARDL bounds test; (ii) in the long run, GHG negatively impacts GDP, RE positively impacts GDP; (iii) in the short run, GHG and RE positively impact GDP; (iv) the speed of adjustment is around 32%. The study holds significance both for scholars and the policy makers from the governmental environment agencies that should decide how to effectively reduce GHG emissions, promote renewable energy adoption, and design policies to facilitate the transition to a low-carbon economy.

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“…, 2019). Among the factors that contribute to the success of Kaizen projects are the appropriate organisational culture and structure (Androniceanu et al. , 2023; Siew Mui et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Kaizen is a Japanese term that means “continuous improvement” and is recognised as a comprehensive quality management approach adopted in most service, commercial and manufacturing industries. This approach eventuates reduced waste in processes and energy consumption and, as a result, increases industries profits (Androniceanu et al. , 2023).…”

Section: Introductionmentioning

confidence: 99%

Measuring the readiness level for Kaizen projects: a multi-layer Bayesian decision-making framework

Amoozad Mahdiraji,

Sharifpour Arabi,

Garza-Reyes

et al. 2023

TQM

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PurposeAcquainting organisations regarding the concepts of Total Quality Management (TQM) and its implementation is one measure that effectively improves their global position and performance. Kaizen is one of the concepts of TQM, which focuses on low-cost organisational transformational methods and often saves consuming significant resources (time, capital, etc.). Using Kaizen in organisational transformation sets efficient guidelines to improve processes agility and leanness and increase manufacturing productivity. Hence, this study aims to identify the key success factors in Kaizen projects and presents a score function that measures the readiness level of organisations to implement Kaizen projects.Design/methodology/approachA literature review first extracts the key success factors in Kaizen projects. Afterwards, the selected factors are screened via the fuzzy Delphi method using expert opinions from the manufacturing sector of an emerging economy. Subsequently, their importance is cross-examined by the Bayesian best–worst Method (BBWM). The BBWM is one of the most recent multiple criteria decision-making (MCDM) methods that lead to stable, dynamic and robust pairwise comparisons. After analysing the weights of the key factors, a score function is designed so that organisations can understand how much they are ready to launch Kaizen projects.FindingsAccording to the findings, “Training and education” and “Employee attitude” played an important role in the success of Kaizen projects. The literature extracted 22 success factors of Kaizen projects, and 10 factors were eliminated through the fuzzy Delphi method. Twelve success factors in Kaizen projects were evaluated and investigated through the BBWM. Matching to this method, “Training and education” and “Employee attitude” weighed 0.119 and 0.112, relatively. Furthermore, “Support from senior management” was the least important factor.Originality/valueTo the best knowledge of the authors, this is the first research in which the success factors of Kaizen projects have been identified and analysed through an integrated multi-layer decision-making framework. Although some studies have investigated the key success factors of Kaizen projects and analysed them through statistical approaches, research that examines the success factors of Kaizen projects through MCDM methods is yet to be reported. Moreover, the score function that measures the level of readiness of each organisation for the successful implementation of Kaizen projects is a unique contribution to this research.

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Increasing Energy Efficiency Based on the Kaizen Approach

Cited by 13 publications

References 73 publications

Implementation of Quality Tools in Mechanical Engineering Piece Production

Implementation of Quality Tools in Mechanical Engineering Piece Production

A Comprehensive Analysis of Renewable Energy Based on Integrating Economic Cybernetics and the Autoregressive Distributed Lag Model—The Case of Romania

Measuring the readiness level for Kaizen projects: a multi-layer Bayesian decision-making framework

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