Sustainable Lean Six-sigma: A new framework for improve sustainable manufacturing performance

DMAIC公司 六西格玛 精益制造 制造工程 持续性 价值流映射 精益六西格玛 索引(排版) 过程管理 绩效指标 过程(计算) 计算机科学 工程类 业务 操作系统 万维网 生物 营销 生态学
作者
Dana Marsetiya Utama,Millenia Abirfatin
出处
期刊:Cleaner engineering and technology [Elsevier BV]
卷期号:17: 100700-100700 被引量:58
标识
DOI:10.1016/j.clet.2023.100700
摘要

Sustainable Manufacturing is essential in supporting a more sustainable production process in the current era. However, continuous improvement research that utilizes Manufacturing Sustainability Index (MSI) scores in improving Sustainable Manufacturing performance is still limited. Therefore, this study aims to propose a new framework for evaluating Manufacturing Sustainability based on lean Six Sigma and sustainable manufacturing concepts using Sustainable Value Stream Mapping (Sus-VSM). We call this new framework Sustainable Lean Six-sigma (SLSS) based on the DMAIC (Define, Measure, Analyze, Improve, Control) approach. The SIPOC diagram and the Delphi method are used in the Define stage to select relevant indicators. Then, the selected indicators were evaluated in the Measure stage, and the Manufacturing Sustainability Index (MSI) was calculated. At the Analyze stage, the Sus-VSM is analyzed. At the Improve stage, improvement proposals are made using Failure Mode and Effect Analysis (FMEA), and a future Sus-VSM is created. Finally, in the Control stage, check sheets are created to control the implementation of the proposed improvements. In the DMAIC process, Sus-VSM is used as a production flow mapping using a traffic light system to map indicators in each process and MSI values on the production line. A case study was also conducted on the Agro-Food Industry. The results showed that the proposed framework could be implemented in the company and successfully improved the Manufacturing Sustainability Index (MSI) score from 88.78% to 93.80%. The implication of this research shows the potential of using the SLSS framework in improving manufacturing sustainability performance in industrial sectors.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
HannahLanguth发布了新的文献求助10
1秒前
TT完成签到,获得积分10
2秒前
多情的忆之完成签到,获得积分10
4秒前
李蕙芯应助chrono采纳,获得10
4秒前
5秒前
千龖完成签到 ,获得积分10
5秒前
hgc完成签到,获得积分10
5秒前
上官若男应助芜湖采纳,获得10
6秒前
相当毛躁完成签到 ,获得积分10
6秒前
哼哼哒完成签到,获得积分10
7秒前
烟花应助黄慧采纳,获得10
7秒前
叶绿体完成签到,获得积分10
7秒前
fuguier发布了新的文献求助10
8秒前
10秒前
平常的冬萱完成签到,获得积分10
10秒前
朴实的千凝完成签到 ,获得积分10
12秒前
江郁清完成签到 ,获得积分10
12秒前
12秒前
Luccvy完成签到,获得积分10
13秒前
yan发布了新的文献求助10
14秒前
14秒前
科目三应助科研通管家采纳,获得30
14秒前
小马甲应助科研通管家采纳,获得10
14秒前
研友_VZG7GZ应助科研通管家采纳,获得10
14秒前
sikh应助科研通管家采纳,获得10
14秒前
14秒前
14秒前
15秒前
nian完成签到,获得积分10
15秒前
Akim应助科研通管家采纳,获得10
15秒前
大个应助科研通管家采纳,获得10
15秒前
Chorsier完成签到,获得积分10
15秒前
深情安青应助科研通管家采纳,获得10
15秒前
Jasper应助科研通管家采纳,获得10
15秒前
15秒前
aaaaaaaaaaaa应助科研通管家采纳,获得10
15秒前
老姜应助科研通管家采纳,获得10
16秒前
华仔应助科研通管家采纳,获得10
16秒前
四喜丸子应助科研通管家采纳,获得10
16秒前
脑洞疼应助科研通管家采纳,获得10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
The Effective Clinical Neurologist 3ed 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7713117
求助须知:如何正确求助?哪些是违规求助? 9268855
关于积分的说明 20074127
捐赠科研通 7289540
什么是DOI,文献DOI怎么找? 3297785
关于科研通互助平台的介绍 2452109
邀请新用户注册赠送积分活动 2304912