Showing papers in "Journal of Manufacturing Systems in 2019"

TL;DR: This research presents an intuitionistic fuzzy TOPSIS method to select the right sustainable supplier that concerns nine criteria and thirty sub-criteria for an automotive spare parts manufacturer and provides an accurate sustainable ranking of suppliers and a reliable solution for sustainable sourcing decisions that is validated through a real-world case study.

TL;DR: In this article, the authors reviewed the last updates on additive manufacturing technologies, material issues, post-processes, and design aspects, particularly in the aviation industry, including various cost models, spare part digitalization and environmental consequences.

TL;DR: The construction of the identification module is based on convolutional neural network, whereas inverted residual block is introduced as the basic block to strike a good balance between identification accuracy and computational efficiency.

TL;DR: Experimental results have proven that the proposed CPMT Platform can significantly improve the overall production efficiency and effectiveness in the shop floor.

TL;DR: This study develops an image-based closed-loop quality control system for a typical AM process, namely, fused filament fabrication (FFF), implemented by a customized online image acquisition system with a proposed image diagnosis-based feedback quality control method.

TL;DR: In this article, a new Corporate Sustainability Assessment (CSA) method for manufacturing companies is proposed, in which sustainability is seen as a process of directed change, assessment tool is designed by modeling manufacturing company using systems representation, and assessment of corporate sustainability (CS) is context-based and linked to SDGs.

TL;DR: In this paper, a multi-sensor system, including an auxiliary illumination (AI) visual sensor system, an UVV band visual sensor, a spectrometer, and two photodiodes, is established to capture signals of the welding status during high-power disk laser welding.

TL;DR: The development of Industry 4.0 is reviewed, along with new and emerging technologies allowing for increased automation, connectivity and flexibility within manufacturing, as well as visual techniques to provide further understanding and clarity of manufacturing processes such as digital twins, virtual and augmented reality.

TL;DR: A cost-driven decision-making framework is proposed to formulate costs of the spatial distribution of microstructural defects and the corresponding control actions, based on in-situ melt pool images, to lay a theoretical foundation for an efficient in-process control strategy, which aims to improve the mechanical properties of fabricated part while maintaining high process throughput.

TL;DR: A multi-agent system composed of several cost effective embedded Arduino systems as agents and a Raspberry-Pi® as a core agent that can reflect the non-linear material value flow without modelling the process or using RFID tags for dynamic value stream mapping (DVSM).

TL;DR: The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.

TL;DR: A new 5-axis path planning model is suggested and developed that takes into account the surface profiles of the freeform part and proposes planning schemes that prevent staircase effects on shell and solid components.

TL;DR: The effectiveness and superior performance of the proposed CBM policy for the serial multistage manufacturing systems is demonstrated through a case study of a serial four-stage machining system producing shaft sleeves.

TL;DR: In this paper, the results of a research project carried out by academic and industrial partners from the German commercial vehicle industry have been presented, which addressed four issues for a long-term application of AM technologies: identification of barriers for AM applications, cost estimation for AM application, design of hybrid additive-subtractive process chains and quality management with AM.

TL;DR: An innovative fog enabled prognosis system for machining process optimization that consists of a terminal layer, a fog layer and a cloud layer to minimize data traffic and improve system efficiency is presented.

TL;DR: This paper investigates machine learning techniques for modeling and predicting the proper printing speed in the CLIP process and shows that the Siamese Network model gives the highest accuracy.

TL;DR: A novel mixed reality-based user interface for quality control inspection which is more intuitive, in order to improve the ergonomics of workers, reduce their stress at work and improve the productivity of current quality control production lines is presented.

TL;DR: A formal modeling approach to configuration of manufacturing enterprises is discussed and it is suggested that the emerging service manufacturing will be open, shared, easy to configurable, efficient, and democratic.

TL;DR: Producibility Index, which is a weighted optimization metric, brings together the quantified outputs of the DFAM analysis, support structure parameters, accessibility analysis and suggests the best build orientations for the given part geometry.

TL;DR: This study proposes the proposed multi-objective particle swarm optimization algorithm with an innovative discrete framework and incorporated with a two-stage approach to search for feasible solutions locally and globally in a novel multi-workshop facility layout problem.

TL;DR: This paper proposes a systematic and data-driven approach for identifying the critical process steps and considers troublesome properties of the data from the process steps such as imbalanced data, missing values, and random sampling.

TL;DR: The developed STAS methodology enhances the current free form surface inspection models, which are mostly based on spatial analysis; into spatio-temporal model, which provides capability to predict the whole part deviation based on partial measurement information and consequently reduces measurement cycle time.

TL;DR: A methodology for the development of a new AM digital chain model, named the Hierarchical Object-Oriented Model (HOOM), based entirely on object-oriented modeling that uses a collection of objects containing stored values of the instance variables found within an object.

TL;DR: This paper proposes an SME-oriented design approach based on a configuration design paradigm that can offer decision support to designers to form flexible architecture for robotic manufacturing systems and, at the same time, give more interactive configuration freedom to customers so as to achieve a high productivity and flexibility for customisation but with less risk and cost of product development.

TL;DR: To obtain a machine configuration (MF) simultaneously having the maximal network reliability and the minimal purchase cost, a two-stage approach is developed based on the non-dominated sorting genetic algorithm II (NSGA-II) and the technique for order of preference by similarity to ideal solution (TOPSIS).

TL;DR: Reading this paper provides readers the foundational knowledge needed to develop intuition and insights on the complexities of stochastic simple serial lines, and serves as a guide to better understand and manage the effects of variability and design factors related to improving serial production line performance.

TL;DR: A service-oriented dynamic multi-level predictive maintenance grouping strategy that is adapted to the SOMA on complex multi-component systems and could provide a feasible and effective long-term dynamic maintenance planning for proactive OEM or PSS providers.

TL;DR: The results have shown that the proposed method has a more realistic impact on component reliability compared to the traditional reliability function and the proposed decision support system outperforms some approaches such as ANN, FMEA, FMECA, and AHP.

TL;DR: A two-phase opportunistic maintenance framework based on defect information is designed, which integrates properties of production waits into the decision-making process and outperforms some classic maintenance policies.

TL;DR: In this article, the authors proposed a robust optimization approach to integrate production and maintenance planning in a multi-state system, where production planning is considered in regard to multi-item capacitated lot sizing problem and maintenance policy is divided into corrective and preventive actions.