scholarly journals Sustainable Decision-Making Approach for Dual-Channel Manufacturing Systems under Space Constraints

2021 ◽  
Vol 13 (20) ◽  
pp. 11456
Author(s):  
P. Mala ◽  
M. Palanivel ◽  
S. Priyan ◽  
N. Anbazhagan ◽  
Srijana Acharya ◽  
...  
Keyword(s):  
Manufacturing Systems ◽  
Sustainable Manufacturing ◽  
Iterative Solution ◽  
Solution Procedure ◽  
Lagrangian Multiplier ◽  
Digital Revolution ◽  
Dual Channel ◽  
Inventory Strategy ◽  
Lagrangian Multiplier Method ◽  
Two Stages

In response to the digital revolution, nowadays, many companies operate online and offline businesses in parallel to ensure their future competitiveness. This research examines the inventory strategy for multi-product vendor-buyer supply chain systems, considering space constraints and carbon emissions, in order to improve competence in managing online and offline integrated orders. We amalgamate costs and emissions in transport and storage. Here, we divide the warehouse of the buyer into two stages: one for satisfying online orders and the other for satisfying offline orders. We also assume that additional crashing costs reduce the lead times for receiving products in the buyer’s warehouse. This study demonstrates a mathematical model in the form of a constrained non-linear programme (NLP) and derives a Lagrangian multiplier method to solve it. An iterative solution procedure is designed in order to attain sustainable manufacturing decisions, which are illustrated numerically.

scholarly journals A mathematical model for designing a reliable cellular hybrid manufacturing-remanufacturing system considering alternative and contingency process routings

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Amirreza Hooshyar Telegraphi ◽  
Akif Asil Bulgak
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Manufacturing Systems ◽  
Closed Loop ◽  
Sustainable Manufacturing ◽  
Critical Issue ◽  
Economic Benefits ◽  
Mixed Integer ◽  
Hybrid Manufacturing ◽  
Closed Loop Supply Chain

AbstractDue to the stringent awareness toward the preservation and resuscitation of natural resources and the potential economic benefits, designing sustainable manufacturing enterprises has become a critical issue in recent years. This presents different challenges in coordinating the activities inside the manufacturing systems with the entire closed-loop supply chain. In this paper, a mixed-integer mathematical model for designing a hybrid-manufacturing-remanufacturing system in a closed-loop supply chain is presented. Noteworthy, the operational planning of a cellular hybrid manufacturing-remanufacturing system is coordinated with the tactical planning of a closed-loop supply chain. To improve the flexibility and reliability in the cellular hybrid manufacturing-remanufacturing system, alternative process routings and contingency process routings are considered. The mathematical model in this paper, to the best of our knowledge, is the first integrated model in the design of hybrid cellular manufacturing systems which considers main and contingency process routings as well as reliability of the manufacturing system.

scholarly journals Self-updated four-node finite element using deep learning

2021 ◽  
Author(s):  
Jaeho Jung ◽  
Hyungmin Jun ◽  
Phill-Seung Lee
Keyword(s):  
Finite Element ◽  
Deep Learning ◽  
Iterative Solution ◽  
Solution Procedure ◽  
Element Formulation ◽  
Zero Energy ◽  
Energy Mode ◽  
Bending Modes ◽  
Solution Accuracy ◽  
Iterative Solution Procedure

AbstractThis paper introduces a new concept called self-updated finite element (SUFE). The finite element (FE) is activated through an iterative procedure to improve the solution accuracy without mesh refinement. A mode-based finite element formulation is devised for a four-node finite element and the assumed modal strain is employed for bending modes. A search procedure for optimal bending directions is implemented through deep learning for a given element deformation to minimize shear locking. The proposed element is called a self-updated four-node finite element, for which an iterative solution procedure is developed. The element passes the patch and zero-energy mode tests. As the number of iterations increases, the finite element solutions become more and more accurate, resulting in significantly accurate solutions with a few iterations. The SUFE concept is very effective, especially when the meshes are coarse and severely distorted. Its excellent performance is demonstrated through various numerical examples.

scholarly journals Special Issue on Smart Sustainable Manufacturing Systems

2019 ◽  
Vol 9 (11) ◽  
pp. 2264
Author(s):  
Gökan May ◽  
Dimitris Kiritsis
Keyword(s):  
Manufacturing Systems ◽  
Sustainable Manufacturing ◽  
Digital Technologies ◽  
Special Issue ◽  
Challenges And Opportunities

With the advent of disruptive digital technologies, companies are facing unprecedented challenges and opportunities [...]

scholarly journals A Review of Engineering Research in Sustainable Manufacturing

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Karl R. Haapala ◽  
Fu Zhao ◽  
Jaime Camelio ◽  
John W. Sutherland ◽  
Steven J. Skerlos ◽  
...  
Keyword(s):  
Decision Making ◽  
Manufacturing Process ◽  
Manufacturing Systems ◽  
Sustainable Manufacturing ◽  
Supply Chain Design ◽  
Planning And Scheduling ◽  
Engineering Research ◽  
Challenges And Opportunities ◽  
Recent Developments ◽  
Planning Development

Sustainable manufacturing requires simultaneous consideration of economic, environmental, and social implications associated with the production and delivery of goods. Fundamentally, sustainable manufacturing relies on descriptive metrics, advanced decision-making, and public policy for implementation, evaluation, and feedback. In this paper, recent research into concepts, methods, and tools for sustainable manufacturing is explored. At the manufacturing process level, engineering research has addressed issues related to planning, development, analysis, and improvement of processes. At a manufacturing systems level, engineering research has addressed challenges relating to facility operation, production planning and scheduling, and supply chain design. Though economically vital, manufacturing processes and systems have retained the negative image of being inefficient, polluting, and dangerous. Industrial and academic researchers are re-imagining manufacturing as a source of innovation to meet society's future needs by undertaking strategic activities focused on sustainable processes and systems. Despite recent developments in decision making and process- and systems-level research, many challenges and opportunities remain. Several of these challenges relevant to manufacturing process and system research, development, implementation, and education are highlighted.

Joint Maintenance and Energy Management of Sustainable Manufacturing Systems

2015 ◽  
Author(s):  
Xufeng Yao ◽  
Zeyi Sun ◽  
Lin Li ◽  
Hua Shao
Keyword(s):  
Decision Making ◽  
Energy Management ◽  
Energy Cost ◽  
Manufacturing Systems ◽  
Sustainable Manufacturing ◽  
Manufacturing Plants ◽  
Machine Reliability ◽  
Automotive Assembly ◽  
Maintenance Decision ◽  
Joint Maintenance

The expenses associated with maintenance activities and energy consumption account for a large portion of the total operation cost in manufacturing plants. Therefore, effective methods that can be used for smart maintenance decision-making and energy management to reduce the costs of these two sections and improve the competitiveness of manufacturing enterprise are of high interests to industry. Many efforts focusing on maintenance decision-making and energy management have been dedicated. However, most of the existing research focusing on these two topics has been conducted separately, very little work has been done from a joint perspective that considers the benefits from both manufacturing machine reliability improvement and energy cost reduction. In this paper, a joint maintenance and energy management method is proposed to identify the maintenance actions considering energy cost as well as other equipment health metrics. A numerical case based on a section of an automotive assembly line is used to illustrate the potential benefits of the proposed approach.

Managing Complexity in Manufacturing Changeovers: A Sustainable Manufacturing-Oriented Approach and the Application Case Study

2016 ◽  
Author(s):  
Khalid Mustafa ◽  
Kai Cheng
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Business Models ◽  
Sustainable Manufacturing ◽  
Lead Times ◽  
Manufacturing Companies ◽  
Factors Affecting ◽  
Manufacturing Complexity ◽  
Oriented Approach

Increasing manufacturing complexity continues to be one of the most significant challenges facing the manufacturing industry today. Due to these rapid changes in manufacturing systems, one of the most important factors affecting production is recognized as the frequent production setup or changeovers, consequently affecting the overall production lead times and competitiveness of the company. Developing responsive production setup and process capability is increasingly important as product ranges and varieties in manufacturing companies are growing rapidly and, at the same time, production business models are operating more towards being customer-oriented. Furthermore, although different conventional methods have been used to manage complexity in production changeovers, sustainability and competitiveness development in a manufacturing company needs to be scientifically addressed by managing manufacturing complexity. In this paper, a sustainable manufacturing-oriented approach is presented in mind of managing manufacturing changeover complexities. A case study is carried out specifically concerning changeover complexity in a pharmaceutical company, aiming at minimizing complexities in production changeover and waste, increasing plant flexibility and productivity, and ultimately the sustainable competitiveness of the company in managing manufacturing changes.

Simulation-Based Optimization of Electricity Demand Response for Sustainable Manufacturing Systems

2014 ◽  
Author(s):  
Leah Cuyler ◽  
Zeyi Sun ◽  
Lin Li
Keyword(s):  
Demand Response ◽  
Manufacturing Systems ◽  
Manufacturing Sector ◽  
Sustainable Manufacturing ◽  
Optimization Method ◽  
Electricity Demand ◽  
System Throughput ◽  
Commercial Building ◽  
Simulation Based ◽  
Simulation Based Optimization

Electricity demand response is considered a promising tool to balance the electricity demand and supply during peak periods. It can effectively reduce the cost of building and operating those peaking power generators that are only run a few hundred hours per year to satisfy the peak demand. The research on the electricity demand response implementation for residential and commercial building sectors has been very mature. Recently, it has also been extended to the manufacturing sector. In this paper, a simulation-based optimization method is developed to identify the optimal demand response decisions for the typical manufacturing systems with multiple machines and buffers. Different objectives, i.e. minimizing the power consumption under the constraint of system throughput, and maximize the overall earnings considering the tradeoff between power demand reduction and potential production loss, are considered. Different energy control decisions are analyzed and compared regarding the potential influence on the throughput of manufacturing system due to the different control actions adopted by throughput bottleneck machine.

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