An integrated SMED-fuzzy FMEA model for reducing setup time

Yazıcı, Kübra; Gökler, Seda Hatice; Boran, Semra

doi:10.1007/s10845-020-01675-x

Cited by 21 publications

(23 citation statements)

References 22 publications

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“…Braglia et al [13] suggest the integration of SMED with the 5-Whys Analysis, which allows to highlight sub-optimum conditions in the changeover process, reducing costs and the effort necessary to conduct the SMED program. Yazıcı et al [14] propose the SMED-fuzzy FMEA to prevent problems causing the extending of the setup time. Azizi and Manoharan [15] designed an efficient VSM (Value Stream Mapping), to improve the productivity of Small and Medium Enterprises.…”

Section: Literature Reviewmentioning

confidence: 99%

“…noticed how there was a subset of workers who were in charge of most changeovers (see operators 1, 7, 8, 9 and 10), while a small subgroup was totally devolved to production only (see operator 2, 4, 13). The remaining workers (namely operator 3,5,6,11,12,14) were hybrid figures who could be involved either in simple setups (e.g., "Basic" or "Hinge Change" type) or in production, with different efficiency (see the green line of production quantity). Similar patterns were recognized across different weekly periods and shifts.…”

Section: Applying Phase Imentioning

confidence: 99%

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The Human-Centric SMED

Fonda

Meneghetti

2022

Sustainability

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The Human-Centric SMED (H-SMED) is an evolution of the classical methodology introduced by Shingo to manage the setup process, which is particularly suitable for companies where the setup involves activities with high human content, that can be hardly transformed into external operations to be performed during the machine uptime. The H-SMED integrates Industry 4.0 tools, as the MES Data Analysis, Lean Management and Ergonomics with a new attention to the centrality of workers, in order to guide the transition towards the next Industry 5.0. The H-SMED methodology is developed into four phases, devolved to: (1) understanding the changeover process; (2) identifying potential improvements; (3) moving from proposal to practice; (4) training and control, in a continuous improvement cycle. The case study of a world-wide known company in the fashion eyewear industry is proposed to validate the framework, reporting a 44% reduction of setup duration.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Applying Phase Imentioning

confidence: 99%

The Human-Centric SMED

Fonda

Meneghetti

2022

Sustainability

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“…This paper showed 57% of mold change time reduction, from 175.9 to 79 minutes, by SMED implementation. On th e other hand, studies performed in similar industries showed a range of 48% to 60% set-up time improvement [18][19][20] [21]. As showed by Yazıcı, Hatice and Boran in which they concluded on an approximate time of 71.32 to 36.97 minutes reduction for an injection molding machine's preparation time [21].…”

Section: A Scenario Vs Outcomesmentioning

confidence: 98%

“…On th e other hand, studies performed in similar industries showed a range of 48% to 60% set-up time improvement [18][19][20] [21]. As showed by Yazıcı, Hatice and Boran in which they concluded on an approximate time of 71.32 to 36.97 minutes reduction for an injection molding machine's preparation time [21]. This investigation is consequent wit h their findings and the other three studies above, thus the validity of the obtained set-up time results is evident.…”

Section: A Scenario Vs Outcomesmentioning

confidence: 99%

Lean-SLP production model to reduce lead time in SMEs in the plastics industry: A Empirical Researh in Peru

Cordova-Pillco¹,

Mendoza-Coaricona²,

Quiroz-Flores³

2022

Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research A

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The current context of the plastic manufacturing sector has suffered a significant alteration in recent years due to external factors such as the pandemic caused by Covid-19. On the other hand, at the national level it has been detected that 64% of companies use only between 61% and 70% of their installed capacity. In addition, the sector's profitability has fallen by 3% in the last 8 years. In this sense, this research work took as a ca se study an SME in the plastic sector to determine the leading ca uses directly related to efficiency and productivity problems. Such causes have resulted in the delayed of delivering orders, consequently lowering profitability; the reversal of loss has been the main incentive of this work. By understanding the roots of the problem, we propose the development of a double-focus optimization model that values both the operational improvement and the working conditions, such as team spirit that motivate the actions of the collaborators. This model utilizes tools corresponding to the L ea n and Systematic Layout Planning (SLP) methodology. Moreover, the novelty of this proposal is the integration of a sustainability phase with a focus on continuous improvement over time by incorporating these tools as part of the company's routine. Finally, some of the main results obtained from this research were an increase of the order fulfillment index by 13.4% , a reduction of the effort of the operators by 62% , a decrease of the set-up time by 57% , and an increase of the Overall Equipment Effectiveness (OEE) by 7% .

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“…Salah satu masalah terbesar di industri automotive adalah pergantian mould, Metode SMED dan 5S dapat menurunkan waktu setup eksternal sebesar 11% (Pinto et al, 2019). Mengintegrasikan metode SMED dengan analisis fuzzy-FMEA dapat mengurangi waktu setup pada produksi plastik injection (Yazıcı et al, 2020). SMED dapat berfungsi mengurangi 6 kerugian utama pada mesin moulding injection sehingga dapat mengurangi waktu setup dan meningkatkan produktivitas sehingga OEE meningkat (Bhade & Hegde, 2020).…”

Section: Pendahuluanunclassified

Peningkatan Produksi Plastik Injection dengan Analisis Overall Equipment Effectiveness dan Single Minute Exchange of Dies

Supriyati

Wiyatno

Darmawan

2021

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The automotive industry is a mainstay because it has a contribution to the national economy. To maintain existence and survive in the midst of intense competition, every industry must be able to continuously improve the quality and performance company in general. Plastic injection manufacturing companies for automotive components are experiencing a decline in machine performance. Machine performance is related to losses that occur in the company. To find out the cause of a decline in machine performance, research is carried out by identifying processes, outputs, losses that occur and taking other actions if needed. Results of OEE calculation analysis, machine 7 has the lowest performance of a total of 8 machines. Low OEE value is influenced by availability, performance, and quality, of three components, the lowest average availability value is only 90%, machine 7 OEE is 81%. Factors affecting OEE are low because the value of availability is low. After analyzing with fishbone diagram, the cause of low availability is due to machine and method factors. Improvement to machine 7 using the SMED method showed a decrease in setup time by 36%, while improvements were made by changing setup flow, replacing machine components, and purging process. Impact of improvements increased availability by 96%, performance, and quality by 99%, while machine efficiency/OEE increased by 93,98%.

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An integrated SMED-fuzzy FMEA model for reducing setup time

Cited by 21 publications

References 22 publications

The Human-Centric SMED

The Human-Centric SMED

Lean-SLP production model to reduce lead time in SMEs in the plastics industry: A Empirical Researh in Peru

Peningkatan Produksi Plastik Injection dengan Analisis Overall Equipment Effectiveness dan Single Minute Exchange of Dies

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