Editorial

2 pages, 199 KiB

Open AccessEditorial

Special Issue on Applied Engineering to Lean Manufacturing and Production Systems 2020

by Jorge Luis García-Alcaraz and Cuauhtémoc Sánchez Ramírez

Appl. Sci. 2022, 12(17), 8897; https://0-doi-org.brum.beds.ac.uk/10.3390/app12178897 - 05 Sep 2022

Cited by 1 | Viewed by 1010

At the end of 2018, a call for papers was made for the Special Issue called “Applied Engineering to Lean Manufacturing Production Systems”, whose objective was to bring together different articles with industrial applications of the different lean manufacturing (LM) tool theories for [...] Read more.

At the end of 2018, a call for papers was made for the Special Issue called “Applied Engineering to Lean Manufacturing Production Systems”, whose objective was to bring together different articles with industrial applications of the different lean manufacturing (LM) tool theories for problem-solving and case studies that improve the indices of the production systems [...] Full article

(This article belongs to the Special Issue Applied Engineering to Lean Manufacturing and Production Systems 2020)

Research

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24 pages, 1755 KiB

Open AccessArticle

Influence of Bottleneck on Productivity of Production Processes Controlled by Different Pull Control Mechanisms

by Nataša Tošanović and Nedeljko Štefanić

Appl. Sci. 2022, 12(3), 1395; https://0-doi-org.brum.beds.ac.uk/10.3390/app12031395 - 28 Jan 2022

Cited by 2 | Viewed by 2241

Abstract

The goal of any lean implementation in production process is achieving better production performances and one of them is productivity. Among many lean principles, pull principle is the most complex to achieve. There are different production control mechanisms for achieving pull and making [...] Read more.

The goal of any lean implementation in production process is achieving better production performances and one of them is productivity. Among many lean principles, pull principle is the most complex to achieve. There are different production control mechanisms for achieving pull and making decision which one to apply can be demanding because sometimes it is not obvious which is the best for specific situation. Many different production parameters influence production process and for one production setting, one control mechanism is the best choice, but for another production setting it might not be. One goal of this study was to research the influence of bottleneck in the production process in regard to achieving better productivity by applying pull principle. Some of the literature considered deals with the topic of bottleneck and pull but focuses only on bottleneck or in addition on one another production parameter and most of the literature studies up to three different pull control mechanisms. One of the objectives of this study was also to fill the research gap in a way to investigate more mechanisms, particularly, according to the literature, those most widely used in various production conditions with emphasis on bottleneck. The advantage of this research is that in addition to the bottleneck, other parameters, namely the number of control cards, variations and processing time are considered. For that reason, simulation experimentation was conducted and as a result regression functions modelling the relationship between productivity and mentioned parameters for four different pull control mechanisms are gained. The analysis showed that the existence of a bottleneck affects the effectiveness of pull mechanisms in terms of productivity. Full article

(This article belongs to the Special Issue Applied Engineering to Lean Manufacturing and Production Systems 2020)

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19 pages, 3197 KiB

Open AccessArticle

System Dynamics and Lean Approach: Development of a Technological Solution in a Regional Product Packaging Company

by Ernesto A. Lagarda-Leyva

Appl. Sci. 2021, 11(17), 7938; https://0-doi-org.brum.beds.ac.uk/10.3390/app11177938 - 27 Aug 2021

Cited by 6 | Viewed by 2682

Abstract

This study was performed in a regional product marketing company located in Ciudad Obregón, Sonora, México, where a problem was detected in empirical decision-making due to their recent incorporation into the market. Thus, the objective of this study is the shelf-product production link, [...] Read more.

This study was performed in a regional product marketing company located in Ciudad Obregón, Sonora, México, where a problem was detected in empirical decision-making due to their recent incorporation into the market. Thus, the objective of this study is the shelf-product production link, where the interest is in knowing the behavior of the main variables that influence the system. System dynamics methodology follows six steps: (1) Map the process under study with the value stream map (VSM); (2) Create a causal diagram; (3) Elaborate the Forrester diagram and equations; (4) Validate the current model; (5) Simulate scenarios; (6) Create the graphical user interface. The main results were the design of the scenarios starting from a robust system dynamics model, three scenarios, and the graphical interface. For this purpose, Stella Architect Software was used as it has special attributes to create a graphical user interface. Furthermore, all the elements of the VSM were added under the Lean Startup approach. Significantly, the inadequate management of the materials was detected, which is why the recommendation was to separate the packaging of dry and cold products to care for food innocuousness and the cold chain. Likewise, processing time decreased, reducing material transfer, which was detected by applying a future VSM based on the Lean Startup methodology. The technological solution in this study is a contribution based on social sciences and mathematics (nonlinear equations) using dynamics simulation to observe the complexity of system behavior. Full article

(This article belongs to the Special Issue Applied Engineering to Lean Manufacturing and Production Systems 2020)

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15 pages, 2497 KiB

Open AccessArticle

PFDA-FMEA, an Integrated Method Improving FMEA Assessment in Product Design

by Pedro Angel García Aguirre, Luis Pérez-Domínguez, David Luviano-Cruz, Jesús Jaime Solano Noriega, Erwin Martínez Gómez and Mauro Callejas-Cuervo

Appl. Sci. 2021, 11(4), 1406; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041406 - 04 Feb 2021

Cited by 17 | Viewed by 3356

Abstract

Product Design (PD) currently faces challenges in new product development, since the industry is in a rush to introduce new products into the market, with customers demanding products that are faster, cheaper, and free from failure. In addition, global companies are trying to [...] Read more.

Product Design (PD) currently faces challenges in new product development, since the industry is in a rush to introduce new products into the market, with customers demanding products that are faster, cheaper, and free from failure. In addition, global companies are trying to improve their product design risk assessment process to gain advantages over competitors, using proven tools like Failure Mode and Effect Analysis (FMEA) and mixing risk assessment methods. However, with current risks assessment tools and a combination of other methods, there is the opportunity to improve risk analysis. This document aims to reveal a novel integrated method, where FMEA, Pythagorean Fuzzy Sets (PFS), and Dimensional Analysis (DA) are cohesive in one model. The proposed method provides an effective technique to identify risks and remove uncertainty and vagueness of human intervention during risk assessment using the Failure Mode and Effect Analysis method. A real-life problem was carried out to illustrate the proposed method. Finally, the study was substantiated by using a correlation and sensitivity analysis, demonstrating the presented integrated method’s usefulness in decision-making and problem-solving. Full article

(This article belongs to the Special Issue Applied Engineering to Lean Manufacturing and Production Systems 2020)

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24 pages, 4250 KiB

Open AccessArticle

Classification and Quantification of Human Error in Manufacturing: A Case Study in Complex Manual Assembly

by Yaniel Torres, Sylvie Nadeau and Kurt Landau

Appl. Sci. 2021, 11(2), 749; https://0-doi-org.brum.beds.ac.uk/10.3390/app11020749 - 14 Jan 2021

Cited by 29 | Viewed by 8776

Abstract

Manual assembly operations are sensitive to human errors that can diminish the quality of final products. The paper shows an application of human reliability analysis in a realistic manufacturing context to identify where and why manual assembly errors occur. The techniques SHERPA and [...] Read more.

Manual assembly operations are sensitive to human errors that can diminish the quality of final products. The paper shows an application of human reliability analysis in a realistic manufacturing context to identify where and why manual assembly errors occur. The techniques SHERPA and HEART were used to perform the analysis of human reliability. Three critical tasks were selected for analysis based on quality records: (1) installation of three types of brackets using fasteners, (2) fixation of a data cable to the assembly structure using cushioned loop clamps and (3) installation of cap covers to protect inlets. The identified error modes with SHERPA were: 36 action errors, nine selection errors, eight information retrieval errors and six checking errors. According to HEART, the highest human error probabilities were associated with assembly parts sensitive to geometry-related errors (brackets and cushioned loop clamps). The study showed that perceptually engaging assembly instructions seem to offer the highest potential for error reduction and performance improvement. Other identified areas of action were the improvement of the inspection process and workers’ provision with better tracking and better feedback. Implementation of assembly guidance systems could potentially benefit worker’s performance and decrease assembly errors. Full article

(This article belongs to the Special Issue Applied Engineering to Lean Manufacturing and Production Systems 2020)

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19 pages, 3809 KiB

Open AccessArticle

Research on Improved OEE Measurement Method Based on the Multiproduct Production System

by Xiaoyan Li, Guangfu Liu and Xinyu Hao

Appl. Sci. 2021, 11(2), 490; https://0-doi-org.brum.beds.ac.uk/10.3390/app11020490 - 06 Jan 2021

Cited by 6 | Viewed by 3893

Abstract

The multiproduct production system has been applied extensively in factories worldwide due to the diverse consumption habits of consumers. However, current Overall Equipment Effectiveness (OEE) measurement methods are not suitable for it properly. With the prevailing of multiproduct production system, it is essential [...] Read more.

The multiproduct production system has been applied extensively in factories worldwide due to the diverse consumption habits of consumers. However, current Overall Equipment Effectiveness (OEE) measurement methods are not suitable for it properly. With the prevailing of multiproduct production system, it is essential to measure the effectiveness accurately in this kind of production system. In order to fill this gap, based on analyzing former OEE models, we propose the multiproduct production system effectiveness (MPSE), including the calculating steps and application framework, in this paper using the heuristic method. This MPSE is verified by a case study. The principal results show that the proposed MPSE can significantly enhance overall production effectiveness and improve the measurement of indicators in the multiproduct production system, which enriches the theory of OEE at the theoretical level and proposes a novel way to measure and improve the effectiveness of the multiproduct production system effectively at the practical level. Full article

(This article belongs to the Special Issue Applied Engineering to Lean Manufacturing and Production Systems 2020)

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13 pages, 6192 KiB

Open AccessArticle

Linear System Identification and Vibration Control of End-Effector for Industrial Robots

by Xiaobiao Shan, Henan Song, Chong Zhang, Guangyan Wang and Jizhuang Fan

Appl. Sci. 2020, 10(23), 8537; https://0-doi-org.brum.beds.ac.uk/10.3390/app10238537 - 29 Nov 2020

Cited by 6 | Viewed by 1935

Abstract

This paper presents the discrete state space mathematical model of the end-effector in industrial robots and designs the linear-quadratic-Gaussian controller, called LQG controller for short, to solve the low frequency vibration problem. Though simplifying the end-effector as the cantilever beam, this paper uses [...] Read more.

This paper presents the discrete state space mathematical model of the end-effector in industrial robots and designs the linear-quadratic-Gaussian controller, called LQG controller for short, to solve the low frequency vibration problem. Though simplifying the end-effector as the cantilever beam, this paper uses the subspace identification method to determine the output dynamic response data and establishes the state space model. Experimentally comparing the influences of different input excitation signals, Chirp sequences from 0 Hz to 100 Hz are used as the final estimation signal and the excitation signal. The LQG controller is designed and simulated to achieve the low frequency vibration suppression of the structure. The results show that the suppression system can effectively suppress the fundamental natural frequency and lower vibration of end-effector. The vibration suppression percentage is 95%, and the vibration amplitude is successfully reduced from ±20 μm to ±1 μm. The present work provides an effective method to suppress the low frequency vibration of the end-effector for industrial robots. Full article

(This article belongs to the Special Issue Applied Engineering to Lean Manufacturing and Production Systems 2020)

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16 pages, 3281 KiB

Open AccessArticle

Dynamic Model and Graphical User Interface: A Solution for the Distribution Process of Regional Products

by Ernesto A. Lagarda-Leyva, Alfredo Bueno-Solano, Harvey P. Vea-Valdez and Daniel O. Machado

Appl. Sci. 2020, 10(13), 4481; https://0-doi-org.brum.beds.ac.uk/10.3390/app10134481 - 28 Jun 2020

Cited by 9 | Viewed by 2802

Abstract

Organizations in the agroindustry sector face shorter delivery schedules; therefore, they are seeking ways to conduct more effective and less costly product distribution. Supply chain management efforts have focused on improving the flow of both products and information. Thus, the aim of this [...] Read more.

Organizations in the agroindustry sector face shorter delivery schedules; therefore, they are seeking ways to conduct more effective and less costly product distribution. Supply chain management efforts have focused on improving the flow of both products and information. Thus, the aim of this case study was to build a graphical user interface to enable decision-making based on quantitative information for a food distribution process. The problem to be solved was associated with the development of a technological solution to reduce and control variations in transportation times, delivery costs and capacities in cold and dry food distribution. An eight-step system for a dynamics methodology was used: (1) distribution process analysis, (2) route description, (3) variable and parameter description, (4) causal loop diagram creation, (5) current model simulation, (6) validation, (7) quantitative scenario construction based on key performance indicators, and (8) graphical user interface development. The main findings of this research were that the graphical user interface and simulation showed information that represented on average 56.49% of the total distribution costs regarding fuel and that maintenance and tire wearing costs had less of an impact on total costs, representing 9.21% and 3.66% of the total costs, respectively. Additionally, the technological solution—created for the supply chain in the distribution process against the background of changes in policies—makes it possible to improve decision-making based on different scenarios supported by a graphical interface according to key performance indicators. This solution could be used by different organizations who aim to reduce logistics and transportation costs. The main implications of this research were the available and organized information and the restructuring of the distribution process. Full article

(This article belongs to the Special Issue Applied Engineering to Lean Manufacturing and Production Systems 2020)

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