Improving the Machining Process of the Metalwork Industry by Upgrading Operative Sequences, Standard Manufacturing Times and Production Procedure Changes

Monteiro, Carlos; Ferreira, Luı́s Pinto; Fernandes, Nuno O.; Silva, Francisco; Amaral, Ivo

doi:10.1016/j.promfg.2020.01.106

Cited by 8 publications

(6 citation statements)

References 13 publications

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“…This urgency becomes more important due to the need to enable the company meet the date agreed upon with the customer. Monteiro et al [53] also used visual management and other Lean tools to reduce the non-conformities in a metalworking firm. The implementation of new procedures has induced a decrease of 2.04% in the non-conformities detected internally and 3.99% in the non-conformities detected by the customer, improving in this way the image of the company and its performance in the market.…”

Section: Discussionmentioning

confidence: 99%

Assessment of the Impact of Lean Tools on the Safety of the Shoemaking Industry

Sá,

Soares,

Dinis-Carvalho

et al. 2023

Safety

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Both the Lean philosophy and occupational safety and health have been widely studied, although this has usually been carried out independently. However, the correlation between Lean and occupational safety and health in the industrial context is still underexplored. Indeed, Lean tools can be applied to ensure the best safety environment for workers in each kind of manufacturing process, and this deserves to be studied. The study described here aims to understand the influence of each of a set of four Lean tools used in an industrial context with a strong manual labor component, seeking to determine the influence of each of these Lean tools on the increase in safety obtained through their application. For this purpose, four Lean tools that are quite commonly applied are selected, taking into account previously presented work that pointed to the positive influence of the application of each of these tools on worker safety: total productive maintenance system, Gemba walk, visual management and Yokoten. This study aims to apply these Lean tools and to analyze their impact on productivity, and then, on the safety of a company selected as a target in order to validate the concept. For this purpose, a new tool is created. In the first instance, the tool analyzes the current state of the productive process and the safety level through the study of the risk levels detected in the plant. In terms of productivity results, a reduction between 7% and 12% in cycle time is achieved in four areas of the plant. The feedback from employees showed increased satisfaction with the processes’ simplification. To conclude, a 50% reduction in the number of work accidents per month is observed as a result of the implementation of Lean tools. The influence of the selected Lean tools on increasing both productivity and safety is clear, and our results prove the selection of tools to be largely adequate.

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Section: Discussionmentioning

confidence: 99%

Assessment of the Impact of Lean Tools on the Safety of the Shoemaking Industry

Sá,

Soares,

Dinis-Carvalho

et al. 2023

Safety

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“…As the level of non-conformity of the product can differ by several different factors, it can be divided into minor non-conformities, major non-conformities and critical non-conformities (Monteiro et al, 2019;Powell et al, 2021;). Minor non-conformities are noticeable, but the product as such can be found on the market at lower prices with an indication that it deviates from the standard (Gamme et al, 2019;).…”

Section: Classification Of Non-conformitiesmentioning

confidence: 99%

“…Product non-conformity can occur for several reasons, the most common of which is due to the failure of the production machine, deviation of the quality of the material from which the product is made, carelessness of employees (Chiu et al, 2018;). Product non-conformity can be expressed in several ways, the basic way is external and internal nonconformity (Chiu et al, 2018;,Monteiro et al, 2019;). External non-conformity is a deviation that is visible, it is most often damage on the surface of the product or semi-finished product in the form of scratches, deviation of shape, dimensions, text, color (Monteiro et al, 2019;).…”

Section: Classification Of Non-conformitiesmentioning

confidence: 99%

“…Product non-conformity can be expressed in several ways, the basic way is external and internal nonconformity (Chiu et al, 2018;,Monteiro et al, 2019;). External non-conformity is a deviation that is visible, it is most often damage on the surface of the product or semi-finished product in the form of scratches, deviation of shape, dimensions, text, color (Monteiro et al, 2019;). While the internal non-conformity refers to the structure of the material, if it is metal casting or plastic injection, there may be air trapped in the product itself (Gamme et al, 2019;).…”

Section: Classification Of Non-conformitiesmentioning

confidence: 99%

“…It is necessary to classify non-conforming products according to the degree of non-conformity and, based on the data, proceed further in accordance with the company's policy (Gamme et al, 2019;). After the non-conformity identification process, it is necessary to mark the non-conforming products based on the classification, which refers to products that can be processed, can be sold as such, but with a note, products that are sent to scrap (Monteiro et al, 2019;Powell et al ., 2021;). Successful classification of nonconforming products can prevent the appearance of nonconforming products on the market, which significantly affects the company's business.…”

Section: Classification Of Non-conformitiesmentioning

confidence: 99%

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Identification of Product Non-Conformities Using Computer Vision Algorithms

Mijailović,

Đorđević,

Stefanović

et al. 2023

J. Eng., Manag. Inf. Technol.

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The implementation of computer vision in the process of identifying non-conforming products, as well as the application of technologies based on Internet networks, deep learning, large databases within the manufacturing industry leads to the emergence of quality 4.0. Today, the application of computer vision as well as non-conformity detection algorithms in the manufacturing industry can be seen as technological pillars of quality 4.0, which is in direct connection with the company's operations. The main goal of the work is the development of a system for identifying non-compliant products within the manufacturing industry, where the focus is on the application of technologies based on computer vision. The secondary goal of the work refers to the reduction of the necessary funds for the implementation of the system on production machines, the development of a universal, flexible system, where the timely identification of non-compliant products will reduce the company's losses.

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