Data driven safe vehicle routing analytics: a differential evolution algorithm to reduce CO2 emissions and hazardous risks

Contemporary vehicle routing requires ubiquitous computing and massive data in order to deal with the three aspects of transportation such as operations, planning and safety. Out of the three aspects, safety is the most vital and this study refers safety as the reduction of CO2 emissions and hazardous risks. Hence, this paper presents a data driven multi-objective differential evolution (MODE) algorithm to solve the safe capacitated vehicle routing problems (CVRP) by minimizing the greenhouse gas emissions and hazardous risk. The proposed data driven MODE is tested using benchmark instances associated with real time data which have predefined load for each of the vehicle travelling on a specific route and the total capacity summed up from the customers cannot exceed the stated load. Pareto fronts are generated as the solution to this multi-objective problem. Computational results proved the viability of the data driven MODE algorithm to solve the multi-objective safe CVRP with a certain trade-off to achieve an efficient solution. Overall the study suggests 5% increment in cost function is essential to reduce the risk factors. The major contributions of this paper are to develop a multi-objective model for a safe vehicle routing and propose a multi-objective differential evolution (MODE) algorithm that can handle structured and unstructured data to solve the safe capacitated vehicle routing problem

Implementation of lean manufacturing and lean audit system in an auto parts manufacturing industry – an industrial case study

Lean manufacturing is one of the innovative manufacturing concepts being applied in many industries to avoid the wastages of resources and improving the quality of products and help the company to become more effective and productive. It also focuses on continuous improvements with the total involvement of all employees with optimum utilization of man power and machine by reducing idle time and reducing lead time with help of lean tools like value stream mapping and kaizen. This paper presents a case study carried out in a foundry division of an auto parts manufacturing industry, where lean tools are implemented for the defect reduction and productivity improvement. In this paper, a conceptualized implementation of total productive maintenance practices of lean tools: Kaizen or continuous improvement and value stream map in an auto parts industry are presented. The result shows improved performance in terms of average core rejections, sand leakage and air lock problem

The LOX-1 Scavenger Receptor and Its Implications in the Treatment of Vascular Disease

Cardiovascular disease is the leading cause of death. The disease is due to atherosclerosis which is characterized by lipid and fat accumulation in arterial blood vessel walls. A key causative event is the accumulation of oxidised low density lipoprotein particles within vascular cells, and this is mediated by scavenger receptors. One such molecule is the LOX-1 scavenger receptor that is expressed on endothelial, vascular smooth muscle, and lymphoid cells including macrophages. LOX-1 interaction with OxLDL particles stimulates atherosclerosis. LOX-1 mediates OxLDL endocytosis via a clathrin-independent internalization pathway. Transgenic animal model studies show that LOX-1 plays a significant role in atherosclerotic plaque initiation and progression. Administration of LOX-1 antibodies in cellular and animal models suggest that such intervention inhibits atherosclerosis. Antiatherogenic strategies that target LOX-1 function using gene therapy or small molecule inhibitors would be new ways to address the increasing incidence of vascular disease in many countries

An improved design for cellular manufacturing system associating scheduling decisions

This paper presents a model for the design of Cellular Manufacturing System (CMS) to evolve simultaneously structural design decisions of Cell Formation (CF) and operational issue decisions of optimal schedule. This integrated decision approach is important for designing a better performing cell. The model allows machine duplication and incorporates cross-flow for scheduling flexibility. The cross-flow is the term introduced to mean the inter-cell movement of parts from parent cell to identical machines in other cells though machines are available in the parent cell. This cross-flow facilitates routing flexibility and paves way for reduced schedule length thereby optimizing resources leading to minimized operational cost. A non-linear integer mathematical programming model is formulated with the objective function of minimizing operating cost which is the sum of Machine Utility Cost (MUC) and inter-cell costs. The MUC is a new cost parameter based on machine utility and it integrates CF, scheduling, and machine duplication decisions. The proposed model belongs to the class of NP-hard problems. A hybrid heuristic (HH) that has “Simulated Annealing Algorithm (SAA) embedded with Genetic Algorithm (GA)” is proposed. A comparison with the mathematical solution reveals that the proposed HH is capable of providing solutions closer to optimal in a computationally efficient manner. The model is validated by studying the effect of integrated decisions, machine duplications, and association of scheduling and cross-flow. The model validation reveals that the proposed CMS model evolves CF, scheduling, and machine duplication decisions with minimum operating cost. Thus, it can be inferred that the proposed model gives optimal integrated decisions for designing an effectively and efficiently performing cells and thus evolves improved CMS design decisions

Identification and evaluation of criteria of agile manufacturing using dematel: a case from an indian metal fabrication industry

In metal fabrication industry, assembling department plays the major role since it involves risks in assembling the components. Hence, it is always difficult for the manufacturers to identify the criteria of agile manufacturing in assembling department that effects the assembly of the fabricated metal components. Agile manufacturing is one of the innovative method of manufacturing, which focus on the customer satisfaction and also maintaining the quality and cost of the product. Metal fabrication industries generally struggle to find right criteria for better agile manufacturing process. This study focuses on the selection of suitable criteria for agile manufacturing, which requires an in-depth analysis depending on the influence they possess on the agile manufacturing. The objective of this paper is to analyze and identify the most influencing criteria for the metal manufacturing industry based on the customers’ and industrial expert’s perspective. Here we have selected ten different criteria based on the literatures available on the agile manufacturing. The criteria are segregated and ranked according to the nature and influence they possess on other criteria using decision making trial and evaluation laboratory (DEMATEL) methodology. This study also helps the metal fabrication industry to identify the most influencing criteria to implement on agile manufacturing and to have high efficiency on the production. The results show that the customer satisfaction seems to be the primary criteria that will have more influence in metal fabrication industry

Analyze the factors influencing human-robot interaction using MCDM method

Robots play a key role in medical equipment manufacturing industry by safeguarding human workers from hazardous environment and risky jobs. Human robot interaction (HRI) is one of the robotic features that are enhanced in industrial robots. They mimic human behavior while arriving at a decision, contributing to the proficiency of the product. Tasks involving human cognitive skills and flexibility in the workers are combined with robots to obtain high-level accuracy, repeatability, and speed. Further, more challenges are to be met for achieving an effective human-robot interaction. In this paper, risk factors affecting the interaction between both robot and humans are discussed, and a contextual case is performed in a top south Indian medical equipment manufacturing industry. Industrial experts' inputs and relevant literature are considered to recognize the risk factors. Multi-Criteria decision-making method (MCDM) like DEMATEL (Decision Making Trial and Evaluation Laboratory) is used to analyze the risk factors influencing HRI in the assembly section. The paper's findings show that automation level and reliability of the robot are the most influential factor in the assembly section and need more attention to control and reduce the risk factor for the effective assembly