The evolution and future of manufacturing: A review

Esmaeilian, Behzad; Behdad, Sara; Wang, Ben

doi:10.1016/j.jmsy.2016.03.001

Cited by 539 publications

(258 citation statements)

References 181 publications

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“…In order to control quality, a plant needs to automatically collect data and history information through sensors and IoT technology, and then analyze and optimize process parameters to adjust them with the actual situation, thereby controlling and improving product quality [86,87]. Therefore, the key to Industry 4.0 is real-time communication and machine to machine connection between all systems [88,89]. Machines and equipment exchange data by communicating with each other, and a "smart" plant can record, analyze and make adjustments on its own to enhance the manufacturing process.…”

Section: Quality Controlmentioning

confidence: 99%

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Tsai

2018

Energies

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Abstract:The textile industry is one of the world's major sources of industrial pollution, and related environmental issues are becoming an ever greater concern. This paper considers the environmental issues of carbon emissions, energy recycling, and waste reuse, and uses a mathematical programming model with Activity-Based Costing (ABC) and the Theory of Constraints (TOC) to achieve profit maximization. This paper discusses the combination of mathematical programming and Industry 4.0 techniques to achieve the purpose of green production planning and control for the textile industry in the new era. The mathematical programming model is used to determine the optimal product mix under various production constraints, while Industry 4.0 techniques are used to control the production progress to achieve the planning targets. With the help of an Industry 4.0 real-time sensor and detection system, it can achieve the purposes of recycling waste, reducing carbon emission, saving energy and cost, and finally achieving a maximization of profit. The main contributions of this research are using mathematical programming approach to formulate the decision model with ABC cost data and TOC constraints for the textile companies and clarifying the relation between mathematical programming models and Industry 4.0 techniques. Managers in the textile companies can apply this decision model to achieve the optimal product-mix under various constraints and to evaluate the effect on profit of carbon emissions, energy recycling, waste reuse, and material quantity discount.

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Section: Quality Controlmentioning

confidence: 99%

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Tsai

2018

Energies

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“…For the development of computer software controlled filament winding machines with high axes, which can automatically apply the software to generate the winding pattern methods [31]. With the software control system and computer numerical control technique has been applied to the manufacturing sector, industrial robots have been employed to replace the traditional filament winding machine [32][33][34]. For industrial winding robots, some detailed knowledge of the robot work principle and the robot language use the RAPID language [35][36][37], which can meet the winding operation.…”

Section: Introductionmentioning

confidence: 99%

Design of portable 3-axis filament winding machine with inexpensive control system

Ma¹,

Rejab²,

Sahat³

et al. 2018

J. MECH. ENG. SCI.

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Filament winding technology is one of the fundamental fabrication methods in composite material fields, which has a high degree of automation. It is the process in which continuous strands or filament of fibres is wound on the mandrel, which is suitable for high-pressure vessels, pipes, shaft and ducts. The present filament winding machines have existed in enterprises or factories, which are high costs, heavy, complex control system and machine structure. The objective of this study is to design a 3-axis filament winding machine, which has portable, lightweight, low costs, high efficient and inexpensive control system features compared to the previous and present machine. The control system relates hardware section and software section, which can meet three axes movement principle. The 3-axis prototype filament winding machine has also been developed. Arduino Uno and CNC v1 shield module are applied as hardware section. Universal G-Code Sender (UGS) and Grbl codes are adopted as software section. In conclusion, a 3-axis portable, lightweight and low-cost filament winding machine have been successfully developed, which can fabricate filament wound carbon/epoxy tubes with a proper inexpensive control system.

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“…Companies in the manufacturing sector face fierce competition from industry rivals as they constantly strive to improve responsiveness to lead times and reducing costs (Staeblein & Aoki, 2015;Esmaeilian, Behdad & Wang, 2016). As a result, the use of operating systems based on JIT (Just-In-Time) has widely spread in order to maintain a stable inventory level (Kumar, 2010;Cedillo-Campos, Sanchez, Vadali, Villa & Menezes, 2014;Vörös & Rappai, 2016).…”

Section: Introductionmentioning

confidence: 99%

Decision policy scenarios for just-in-sequence (JIS) deliveries

Cedillo-Campos¹,

Ruelas²,

Lizárraga-Lizárraga³

et al. 2017

JIEM

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Abstract:Purpose: The Just-in-Sequence (JIS) approach is evidencing advantages when controlling costs due to product variety management, and reducing the risk of disruption in sourcing, manufacturing companies and third-party logistics (3PL). This has increased its implementation in the manufacturing industry, especially in highly customized sectors such as the automotive industry. However, despite the growing interest from manufacturers, scholarly research focused on JIS still remains limited. In this context, little has been done to study the effect of JIS on the fluidity of supply chains and processes of logistics suppliers as well as providing them with a decision making tool to optimise the sequencing of their deliveries. Therefore, the aim of this paper is to propose a genetic algorithm to evaluate different decision policy scenarios to reduce risks of supply disruptions at assembly line of finished goods. Consequently, the proposed algorithm considers a periodic review of the inventory that assumes a steady demand and short response times is developed and applied.-581-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.2090Design/methodology/approach: Based on a literature review and real-life information, an abductive reasoning was performed and a case study application of the proposed genetic algorithm conducted in the automotive industry. Findings:The results obtained from the case study indicate that the proposed genetic algorithm offers a reliable solution when facing variability in safety stocks that operate under assumptions such as: i) fixed costs; ii) high inventory turnover; iii) scarce previous information concerning material requirements; and iv) replenishment services as core business value. Although the results are based on an automotive industry case study, they are equally applicable to other assembly supply chains.Originality/value: This paper is of interest to practitioners and academicians alike as it complements and supports the very limited scholarly research on JIS by providing manufacturers and 3PL suppliers competing in mass customized industries and markets, a decision support system to help decision making. Implications for the design of modern assembly supply chains are also exposed and future research streams presented.

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The evolution and future of manufacturing: A review

Cited by 539 publications

References 181 publications

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Design of portable 3-axis filament winding machine with inexpensive control system

Decision policy scenarios for just-in-sequence (JIS) deliveries

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