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Nowadays, the survival and success of companies depend on improving on-time delivery and cost reduction. To reach this target, it is necessary to get improvements, standardization, and controlling of the manufacturing systems. Therefore, the objective of this scientific work is to perform a case study, based on the implementation of new single-minu...
Citations
... Activity logic optimization is the basis of other optimization approaches, such as resource allocation optimization, time optimization and cost optimization. The eliminate, combine, rearrange, and simplify (ECRS) analysis technique is regarded as an effective method for improving activity logic [48][49][50]. Therefore, the ECRS analysis technique has the potential to be used in combination with intelligent simulation technology to improve construction performance. ...
The construction of prefabricated buildings involves complex processes, which have high uncertainties and objective conflicts, hindering the improvement of construction performance. This study aims to simultaneously optimize the activity logic and multiple construction performance objectives (concerning time, cost, quality, and CO2 emissions) of prefabricated building construction under the influence of uncertain factors. The eliminate, combine, rearrange, and simplify (ECRS) technique is combined with intelligent simulation technology to develop a simulation-based optimization method for prefabricated building construction considering multiple objectives and various uncertain factors. This method is characterized by enabling activity-logic improvements, revealing mathematical relationships between uncertain factors, activity parameters and construction performance, and achieving the trade-off optimization of construction performance objectives in various uncertain environments. A typical prefabricated building project is used for demonstrating and validating the method. The results show that the proposed method reduces the construction time by 5.73% through the ECRS technique, and further achieves a 10.53% reduction in construction cost, a 10.10% improvement in construction quality, and 60.32% CO2 emission mitigation through multiobjective optimization when only resource allocation is considered. Considering the interaction between resource allocation conditions and other three uncertain factors, the construction time is mainly affected by the supply of materials and weather conditions, while the familiarity level of work affects the construction time, cost, and CO2 emissions. The proposed method and findings of this study can facilitate robust decision-making by project managers when addressing the trade-offs between cost reduction, schedule shortening, quality improvement, and CO2 reduction under various uncertain scenarios.
... Furthermore, productivity also increased by 10%. Junior et al. [47] used SMED methodology in an oil and gas company to increase its performance and reported that after the implementation of SMED, there was a significant improvement of 91.6% in setup time, decreasing from 1 hour 44 minutes 56 seconds (6,296 seconds) to 8 minutes 52 seconds (532 seconds). Additionally, a significant increase of 44.6% in overall equipment effectiveness OEE was observed and setup activities were standardized, ensuring consistency and efficiency. ...
... Moreira et al. [52] have also reported an improvement in OEE based on the application of LM in the manufacturing industry. OEE is a key indicator that highlights the performance of industries [45][46][47]. Arun et al. [28] also reported that breakdowns play a vital role in equipment performance. Through their analysis, they have found that by reducing breakdowns, OEE can be increased. ...
... Methodology Results Mendhe and Rathi [6] SMED implementation OEE improved by 10% Rehman et al. [9] TPM implementation OEE improved by 9.6% Arun et al. [28] TPM implementation OEE improved by 7 % Ovedje et al. [31] TPM implementation OEE improved by 22 % Morales and Silva [46] SMED implementation OEE improved by 9.5% Junior et al. [47] SMED implementation OEE improved by 44.6% Zulfikar et al. [48] TPM implementation OEE improved by 10.53% Vieira et al. [54] SMED implementation OEE improved by 10.8% Present study SMED and TPM implementation OEE improved by 30.30% ...
This study aims to reduce downtime in the rolling mill and improve equipment availability. The primary objective is to enhance the productivity of the rolling mill by implementing lean manufacturing methods, specifically single-minute exchange of die (SMED) and total productive maintenance (TPM). Following the implementation of SMED and TPM, the availability and productivity of the rolling mill improved by approximately 11.37% and 5%, respectively. Moreover, the average overall equipment efficiency (OEE) witnessed a significant
improvement of about 30.30%, rising from 56.42% to 73.52%. This enhanced OEE can be attributed to the reduction in section changeover time and a decrease in breakdowns.
... Then, it employs proper strategies such as duplication, parallel execution and standardization, for converting internal activities to external ones and streamlining both of them to minimize production stoppage . SMED implementation has been reported and studied in various industries such as automotive (Cakmakci, 2009), food (Lozano et al., 2017), oil and gas (Junior et al., 2022). Regarding the importance of quality management to increase the productivity, profitability and sustainability of manufacturing processes , setup operations also play an important role in enhancing this concept accomplishment in manufacturing processes. ...
... It also affects other criteria such as overall equipment effectiveness (Lozano et al., 2017), inventory level, energy consumption, productivity (Belhadi et al., 2018) and total production lead time . Hence, the literature addresses application strategies such as working method, knowledge management, organizational design (Stapelbroek et al., 2022) and the most common one, i.e. standardization (Braglia et al., 2016;Junior et al., 2022;Mukhopadhyay and Shanker, 2005) which provide remarkable opportunities to overcome product losses and achieve the desired product quality in setup operations. In this vein, a desirable setup operation must guarantee the quality of product after startup of the machine, besides reducing the setup time. ...
... (2) Considering the conventional application strategies in SMED implementation such as parallel execution (Mukhopadhyay and Shanker, 2005), duplication (Braglia et al., 2016) and standardization (Junior et al., 2022), SMED 4.0 also employs predict-prevent strategies to avoid defect occurrence during the production. ...
Purpose
This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.
Design/methodology/approach
The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.
Findings
It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.
Originality/value
The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.
... Then, it employs proper strategies such as duplication, parallel execution and standardization, for converting internal activities to external ones and streamlining both of them to minimize production stoppage . SMED implementation has been reported and studied in various industries such as automotive (Cakmakci, 2009), food (Lozano et al., 2017), oil and gas (Junior et al., 2022). Regarding the importance of quality management to increase the productivity, profitability and sustainability of manufacturing processes , setup operations also play an important role in enhancing this concept accomplishment in manufacturing processes. ...
... It also affects other criteria such as overall equipment effectiveness (Lozano et al., 2017), inventory level, energy consumption, productivity (Belhadi et al., 2018) and total production lead time . Hence, the literature addresses application strategies such as working method, knowledge management, organizational design (Stapelbroek et al., 2022) and the most common one, i.e. standardization (Braglia et al., 2016;Junior et al., 2022;Mukhopadhyay and Shanker, 2005) which provide remarkable opportunities to overcome product losses and achieve the desired product quality in setup operations. In this vein, a desirable setup operation must guarantee the quality of product after startup of the machine, besides reducing the setup time. ...
... (2) Considering the conventional application strategies in SMED implementation such as parallel execution (Mukhopadhyay and Shanker, 2005), duplication (Braglia et al., 2016) and standardization (Junior et al., 2022), SMED 4.0 also employs predict-prevent strategies to avoid defect occurrence during the production. ...
Purpose
This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.
Design/methodology/approach
The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.
Findings
It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.
Originality/value
The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.
... The main results obtained from the study indicate that the preparation times of the machines were reduced by more than 45% for the turning line. Similarly, [14] applied SMED, in an oil and gas company. The findings achieved in this work showed that the preparation time was improved by 91.6%, from 1 h 44 min 56 s to 8 min 52 s, and the OEE increased by 44.6%. ...
... [13] Junior, Inácio, da Silva, Hassui & Barbosa (2022) They applied SMED, in an oil and gas company. [14] Fonda, & Meneghetti (2022) They state, the Human-Centric SMED (H-SMED) is an evolution of the classic methodology introduced by Shingo to manage the installation process, it involves activities with a high human content, which can hardly be transformed into external operations. [16] Utiyama, Godinho Filho & Oprime (2021) They propose an alternative approach to improve manufacturing lead time and time between failures. ...
... Over the past 2 decades, the literature dealing on SMED has expanded significantly, reflecting the growing need to reduce product set-up times. As a result, SMED has become one of the most widely recognized tools of the Lean philosophy by companies worldwide (Benjamin et al., 2013;Junior et al., 2022). There are three key reasons why companies strive to reduce set-up times and adopt the SMED approach (Van Goubergen and Van Landeghem, 2002): ...
... The SMED methodology is widely supported in both the academic and industrial literature (Junior et al., 2022). Today, implementing SMED is the natural evolution of the original formulation by Shingo (1985), thanks to the integration of Lean Manufacturing and the new possibilities introduced by Industry 4.0, also referred to as smart manufacturing (Buer et al., 2018;Pagliosa et al., 2021;Sanders et al., 2016). ...
Purpose
This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines in terms of rapid changeover capability.
Design/methodology/approach
To improve the performance in terms of set up time, QCD addresses machine design from a single-minute digit exchange of die (SMED). Although conceived to aid the design of completely new machines, QCD can be adapted to support for simple design upgrades on pre-existing machines. The QCD is structured in three consecutive steps, each supported by specific tools and analysis forms to facilitate and better structure the designers' activities.
Findings
QCD helps equipment manufacturers to understand the current and future needs of the manufacturers' customers to: (1) anticipate the requirements for new and different set-up process; (2) prioritize the possible technical solutions; (3) build machines and equipment that are easy and fast to set-up under variable contexts. When applied to a production system consisting of machines subject to frequent or time-consuming set-up processes, QCD enhances both responsiveness to external market demands and internal control of factory operations.
Originality/value
The QCD approach is a support system for the development of completely new machines and is also particularly effective in upgrading existing ones. QCD's practical application is demonstrated using a case study concerning a vertical spindle machine.
... Changeover is one of the most time-consuming, no-value-added activities in several manufacturing environments [1]. Lean manufacturing aims at maximizing the value of the product through the minimization of no-value-added activities and dedicates particular attention to set-up time reduction to get rapid changeover of dies and equipment [2]. ...
... Again, Braglia et al. [22] proposed an integrated approach to enhance the conventional SMED. Recently, Pattaro Junior et al. [2] developed a framework based on a practical application of strategies such as improvements by ECRS (eliminate, combine, reduce, and simplify), Standardized Work (SW), and Overall Equipment Effectiveness (OEE). ...
The ability of companies to rapidly conduct a changeover from one product to another as part of a production process is a fundamental step towards a more flexible production system that can deal with an increasingly dynamic and competitive market. Single-Minute Exchange of Die (SMED) is the best-known lean tool that aims to reduce time consumption in the changeover process. This paper presents a new Lean tool called Set-up Saving Deployment (SSD), which improves set-up efficiency by classifying, analyzing, and removing set-up losses within a changeover process, and which supports decision-making for SMED implementation. SSD uses three matrices, constructed sequentially from the first (L-Matrix) to the last (ECE-Matrix), in order to assess the possible time savings that can be achieved by eliminating losses and, in addition, to forecast possible improvements resulting from implementing a SMED project. SSD also provides a new basket of tailored set-up efficiency indicators that allow the analysis team to correctly assess set-up efficiency, and compare the 'as is' condition with the subsequent 'to be' condition from an operational perspective. The effectiveness of SSD in addressing set-up losses and predicting time savings is illustrated using an industrial case study of a resin doming machine. Thanks to its structured step-by-step procedure, SSD significantly improves the efficiency of the changeover process.
... However, reviews on rapid setup are inadequate. Most of them focus on a particular method or theory, such as single minute exchange of die (SMED) (Joshi and Naik, 2012;Martins et al., 2018;Pattaro et al., 2022;da Silva and Godinho, 2019) and design for changeover (DFC) (Reik, 2007;Reik et al., 2006b;Reik et al., 2006a;Reik et al., 2005;Karekatti and Wickramasinghe, 2021). They lack the support of specific data sets from a holistic perspective. ...
Purpose
This paper aims to systematically understand the development of rapid setup, quantitatively analyze the landscape and reveal new trends and challenges.
Design/methodology/approach
Based on 192 literature studies (1987–2021) collected from Scopus and Google Scholar, the papers are classified by: publication time and source; research type and data analysis of papers; pattern of authorship and country; sector-wise focus of the paper; improvement method used in the setup. And CiteSpace is used to analyze the cooccurrence and timeline of keywords.
Findings
There has been substantial progress in the past 35 years, including the rapid growth in the number of papers, the expansion in different disciplines, the participation of developing countries, the application in the service industry and the significant impact of setup on cost. And there are still some deficiencies.
Research limitations/implications
There is concern that Google Scholar lacks the quality control needed for its use as a bibliometric tool. Future work is encouraged to conduct an in-depth discussion on high-quality papers.
Practical implications
In small batch production, rapid setup is increasingly essential. Clarifying the research focus and main improvement methods is of great significance for enterprises to meet the changing market needs.
Originality/value
To the best of the authors’ knowledge, this study is the first literature review on rapid setup. It is decided to consider a detailed set of data for better introspection and trace the history reflections and the research future in setup time.
... The SMED tool consists of a system to reduce setup time [38] and changeover times by simplifying processes, eliminating unnecessary procedures, and standardizing work [39]. This tool aims to reduce waste in the production system by preparing equipment and/or tasks and performing quick changeovers, i.e., with a duration of 9 min or less (corresponding to a number of minutes of only one digit) [40]. ...
Although Lean Thinking (LT) is becoming popular in service organizations, few studies have applied Lean tools to the education sector. Furthermore, although inventories are one of the main wastes in this sector, to date, no study has presented a decision support system (DSS), based on LT, for stock management in academic institutions. This study aims to design an application of LT in teaching and research laboratories to provide improvements in workplace organization, setup times, and stock management. Lean tools were implemented in a case study, and an e-Kanban DSS was designed to determine when and in what quantity an order should be placed, considering factors such as forecasting demand, demand level (high or low), and component deterioration. For testing the DSS, a simulation was carried out using as an example a set of articles that integrate the protocol of laboratory activity. The implementation of Lean tools improved the organization of the workplace, which contributed to a reduction in unnecessary movements and the setup time of practical activities. Additionally, the study demonstrated that the developed DSS calculates the quantities to be ordered according to the selected mathematical formulas and generates appropriate visual alerts, depending on the need to place an order.
... Studies shows the development based on an application of improvement by ECRS (eliminate, combine, reduce, and simplify), standardized work (SW) and OEE. The combination achieve that the Set-up time was improved by 91.6 %, OEE increased by 44.6 % and the setup activities were standardized [21]. ...
