Vehicle Assembly Line Research Articles

On Energy Consumption and Productivity in a Mixed-Model Assembly Line Sequencing Problem

Mixed and multi-model assembly line sequencing problems are more practical than single-product models. The methods and selection criteria used must keep up with the constantly increasing level of variability, synchronize flows between various—often very energy-intensive production departments—and cope with high dynamics resulting from interrupted supply chains. The requirements for conscious use of Earth’s limited natural resources and the need to limit energy consumption and interference in the environment force the inclusion of additional evaluation criteria focusing on the environmental aspect in optimization models. Effective sustainable solutions take into account productivity, timeliness, flow synchronization, and the reduction of energy consumption. In the paper, the problem of determining the sequence of vehicles for a selected class of multi-version assembly lines, in which the order restrictions were determined taking into account the above criteria, is presented. Original value of the paper is the development of the Grey Wolf Optimizer (GWO) for the mixed-model assembly lines sequencing problem. In the paper, a comparative analysis of the greedy heuristics, Simulated Annealing and GWO for a real case study of a mixed vehicle assembly line is presented. The GWO outperforms other algorithms. Overall research performance of the GWO on the sequencing problem is effective.

Comparison of 3D Sensors for Automating Bolt-Tightening Operations in the Automotive Industry.

Machine vision systems are widely used in assembly lines for providing sensing abilities to robots to allow them to handle dynamic environments. This paper presents a comparison of 3D sensors for evaluating which one is best suited for usage in a machine vision system for robotic fastening operations within an automotive assembly line. The perception system is necessary for taking into account the position uncertainty that arises from the vehicles being transported in an aerial conveyor. Three sensors with different working principles were compared, namely laser triangulation (SICK TriSpector1030), structured light with sequential stripe patterns (Photoneo PhoXi S) and structured light with infrared speckle pattern (Asus Xtion Pro Live). The accuracy of the sensors was measured by computing the root mean square error (RMSE) of the point cloud registrations between their scans and two types of reference point clouds, namely, CAD files and 3D sensor scans. Overall, the RMSE was lower when using sensor scans, with the SICK TriSpector1030 achieving the best results (0.25 mm ± 0.03 mm), the Photoneo PhoXi S having the intermediate performance (0.49 mm ± 0.14 mm) and the Asus Xtion Pro Live obtaining the higher RMSE (1.01 mm ± 0.11 mm). Considering the use case requirements, the final machine vision system relied on the SICK TriSpector1030 sensor and was integrated with a collaborative robot, which was successfully deployed in an vehicle assembly line, achieving 94% success in 53,400 screwing operations.

Development of framework for armoured vehicle assembly line efficiency improvement by using simulation analysis: Part 1

Efficiencies and the productivity of the assembly line are crucial in the manufacturing sector. It is very unusual opportunity to visualise and analyse the production system, which used in defence manufacturing sector. This research study focuses on the performance of an existing production line for Malaysia’s automotive defence manufacturing industry. The main issues that arise are first, the delivery is always behind the schedule and second, the human factor that contributes to the increase of rejected parts and slow down the production line. WITNESS simulation will be utilised to analyse the dynamic issues associated with the whole performance of the manufacturing system. A methodology for production layout improvement will bring into notice. DELMIA simulation can improve employee’s working condition, which is to optimise the production line efficiency. The assembly line can be better in many ways, for example, the arrangement of working layout, the summit of the workplace and massive machines handling method by the worker. All of these are imperative to increase the efficiency of the employees. Continuous improvement of the proposed methodology includes progress in model design, training of operators, follow-up of implementing changes and investigations in the measurement of manufacturing line efficiencies.

Performance analysis of vehicle assembly line using discrete event simulation modelling

The purpose of this paper is to utilise simulation as a decision making tool in a complex manufacturing setup. A vehicle assembly line at an automobile company in India is modelled and analysed to help managers to identify the criticality of different parameters. Conveyor speed, operator fatigue and incoming material quality were selected from a pool of parameters which affect the line output. On the basis of design of experiments (DOE), experiments were carried out to capture the effect of input parameters on the line output. The results from these were further analysed using response surface methodology (RSM) and analysis of variance (ANOVA). The line output was found to be most sensitive to operator fatigue followed by incoming material quality and conveyor speed. This paper provides a structured approach to analyse the vehicle assembly line in an automobile company and provides a suitable tool to the management to analyse the complex functioning of a manufacturing system.

Performance analysis of vehicle assembly line using discrete event simulation modelling

The purpose of this paper is to utilise simulation as a decision making tool in a complex manufacturing setup. A vehicle assembly line at an automobile company in India is modelled and analysed to help managers to identify the criticality of different parameters. Conveyor speed, operator fatigue and incoming material quality were selected from a pool of parameters which affect the line output. On the basis of design of experiments (DOE), experiments were carried out to capture the effect of input parameters on the line output. The results from these were further analysed using response surface methodology (RSM) and analysis of variance (ANOVA). The line output was found to be most sensitive to operator fatigue followed by incoming material quality and conveyor speed. This paper provides a structured approach to analyse the vehicle assembly line in an automobile company and provides a suitable tool to the management to analyse the complex functioning of a manufacturing system.

Smart Information Visualization for First-Time Quality within the Automobile Production Assembly Line

This paper presents a smart information technology framework for an adequate visualization of assembly- and quality-related information on the vehicle assembly line. Automobile manufacturers face challenges in control of the increasing variety of products and the resulting high complexity of production. As a result, due to the high proportion of manual work in vehicle assembly, correct information is particularly necessary at the right time, in the right place and in the right form for the users. Despite technological advances for the visualization of information in the industrial sector, there is no adequate logical and information technology structure for the visualization of assembly- and quality-related information in automobile production. As a solution, the information technology framework in this paper provides users with role-, work-and time-oriented information through sufficient tools. The existing problems resulting from a lack of digital user assistance are thus to be prevented, resulting quality defects are to be avoided with regard to first-time quality and the overall efficiency of production is to be increased. In general, this framework contributes in the transformation to a quality-oriented smart factory and an intensive man-system collaboration.

Assembly line performance and modeling

Automobile sector forms the backbone of manufacturing sector. Vehicle assembly line is important section in automobile plant where repetitive tasks are performed one after another at different workstations. In this thesis, a methodology is proposed to reduce cycle time and time loss due to important factors like equipment failure, shortage of inventory, absenteeism, set-up, material handling, rejection and fatigue to improve output within given cost constraints. Various relationships between these factors, corresponding cost and output are established by scientific approach. This methodology is validated in three different vehicle assembly plants. Proposed methodology may help practitioners to optimize the assembly line using lean techniques.

Cost models for improved vehicle assembly line performance

The viability of any manufacturing plant is a function of time and cost. Automobile manufacturing is the most competitive sector. The objective of this paper is to provide a detailed description of the development of the relationships between cost of failure and time lost due to equipment failure, cost of inventory and time lost due to shortages of material, cost of set up and time lost due to set up, cost of absenteeism and time lost due to absenteeism, and cost of material handling and time lost due to material handling. Relationships are established scientifically using regression modelling, simulation and discussions with domain experts. Results are validated in an operational vehicle assembly line. The results demonstrate that the established models follows a cubic relationship as against the hyperbolic relationship previously reported in literature. Further, an improved model strong 17 strong constraints is presented which may be useful for managers in taking cost-based decisions to improve the throughput.

Cost models for improved vehicle assembly line performance

The viability of any manufacturing plant is a function of time and cost. Automobile manufacturing is the most competitive sector. The objective of this paper is to provide a detailed description of the development of the relationships between cost of failure and time lost due to equipment failure, cost of inventory and time lost due to shortages of material, cost of set up and time lost due to set up, cost of absenteeism and time lost due to absenteeism, and cost of material handling and time lost due to material handling. Relationships are established scientifically using regression modelling, simulation and discussions with domain experts. Results are validated in an operational vehicle assembly line. The results demonstrate that the established models follows a cubic relationship as against the hyperbolic relationship previously reported in literature. Further, an improved model strong 17 strong constraints is presented which may be useful for managers in taking cost-based decisions to improve the throughput.

Improving Energy Efficiency for the Vehicle Assembly Industry: A Discrete Event Simulation Approach

This paper presented a Discrete Event Simulation (DES) model for investigating and improving energy efficiency in vehicle assembly line. The car manufacturing industry is one of the highest energy consuming industries. Using Rockwell Arena DES package; a detailed model was constructed for an actual vehicle assembly plant. The sources of energy considered in this research are electricity and fuel; which are the two main types of energy sources used in a typical vehicle assembly plant. The model depicts the performance measurement for process- specific energy measures of painting, welding, and assembling processes. Sound energy efficiency model within this industry has two-fold advantage: reducing CO2 emission and cost reduction associated with fuel and electricity consumption. The paper starts with an overview of challenges in energy consumption within the facilities of automotive assembly line and highlights the parameters for energy efficiency. The results of the simulation model indicated improvements for energy saving objectives and reduced costs.

Modeling Energy Efficiency As A Green Logistics Component In Vehicle Assembly Line

This paper uses System Dynamics (SD) simulation to investigate the concept green logistics in terms of energy efficiency in automotive industry. The car manufacturing industry is considered to be one of the highest energy consuming industries. An efficient decision making model is proposed that capture the impacts of strategic decisions on energy consumption and environmental sustainability. The sources of energy considered in this research are electricity and fuel; which are the two main types of energy sources used in a typical vehicle assembly plant. The model depicts the performance measurement for process- specific energy measures of painting, welding, and assembling processes. SD is the chosen simulation method and the main green logistics issues considered are Carbon Dioxide (CO2) emission and energy utilization. The model will assist decision makers acquire an in-depth understanding of relationship between high level planning and low level operation activities on production, environmental impacts and costs associated. The results of the SD model signify the existence of positive trade-offs between green practices of energy efficiency and the reduction of CO2 emission.

Parallel autonomous guided vehicle assembly line for a semi-continuous manufacturing system

Purpose This paper aims to propose a parallel automated assembly line system to produce multiple products in a semi-continuous system. Design/methodology/approach The control system developed in this research consists of a manufacturing system for two-level hierarchical dynamic decisions of autonomous/automated/automatic-guided vehicles (AGVs) dispatching/next station selection and machining schedules and a station control scheme for operational control of machines and components. In this proposed problem, the assignment of multiple AGVs to different assembly lines and the semi-continuous stations is a critical objective. AGVs and station scheduling decisions are made at the assembly line level. On the other hand, component and machining resource scheduling are made at the station level. Findings The proposed scheduler first decomposes the dynamic scheduling problems into a static AGV and machine assignment during each short-term rolling window. It optimizes weighted completion time of tasks for each short-term window by formulating the task and resource assignment problem as a minimum cost flow problem during each short-term scheduling window. A comprehensive decision making process and heuristics are developed for efficient implementation. A simulation study is worked out for validation. Originality/value Several assembly lines are configured to produce multiple products in which the technologies of machines are shared among the assembly lines when required. The sequence of stations is pre-specified in each assembly line and the components of a product are kept in machine magazine. The transportation between the stations in an assembly line (intra assembly line) and among stations in different assembly lines (inter assembly line) are performed using AGVs.

Mathematical modelling of vehicle assembly line for throughput enhancement

The objective of this work is to improve the performance of vehicle assembly line by developing suitable mathematical relations between various influencing parameters affecting throughput. This work also systematically identifies and describes different approaches adopted by various research scholars through systematic review of peer-reviewed papers from reputable journals. There are several uncertainties in manufacturing environments. Here, mathematical models are developed to consider the impact of important influencing factors like equipment failure, short supply of material, absenteeism, set-up, material handling, rejection and fatigue on throughput. Then, inter-relationships are established between these parameters. Relationships between these parameters and their corresponding cost are also developed. Relationships are established scientifically using regression modelling, MATLAB, Minitab, Excel, Arena and discussions with domain experts. These are validated with real world data. Practitioners may use these models to predict and control uncertainty. Further, within a given cost constraint and using lean techniques, cycle time may be reduced.

Lean Manufacturing Implementation Through Value Stream Mapping: A Case Study

Lean Manufacturing (LM) is a business strategy that was developed in Japan. The main contribution of lean manufacturing is the identification and elimination of waste. Companies apply LM to sustain their competitiveness over their competitors by improving the manufacturing system’s productivity and quality enhancement of the product. The goal of this paper is to apply one of the most significant lean manufacturing techniques called Value Stream Mapping (VSM) to improve the production line of a company that produces several components for vehicle assembly line by decreasing the waste and non-value added activities. First, the current value stream map of production line was developed using personal interviews, observations and secondary data of the company. Subsequently, the future value stream map was proposed based on the lean manufacturing principles to improve total production lead time and value added time. Based on the final result it can be concluded that VSM is a useful and applicable approach that can help managers conceptualize the different kind of wastes and defects. Final result showed that the production lead time and value added time improved up to nearly 80 % and 12 % respectively by eliminating the wastes based on lean principles and VMS method.

Throughput centered prioritization of machines in transfer lines

In an environment of scarce resources and complex production systems, prioritizing is key to confront the challenge of managing physical assets. In the literature, there exist a number of techniques to prioritize maintenance decisions that consider safety, technical and business perspectives. However, the effect of risk mitigating elements—such as intermediate buffers in production lines—on prioritization has not yet been investigated in depth. In this line, the work proposes a user-friendly graphical technique called the system efficiency influence diagram (SEID). Asset managers may use SEID to identify machines that have a greater impact on the system throughput, and thus set prioritized maintenance policies and/or redesign of buffers capacities. The tool provides insight to the analyst as it decomposes the influence of a given machine on the system throughput as a product of two elements: (1) system influence efficiency factor and (2) machine unavailability factor. We illustrate its applicability using three case studies: a four-machine transfer line, a vehicle assembly line, and an open-pit mining conveyor system. The results confirm that the machines with greater unavailability factors are not necessarily the most important for the efficiency of the production line, as it is the case when no intermediate buffers exist. As a decision aid tool, SEID emphasizes the need to move from a maintenance vision focused on machine availability, to a systems engineering perspective.

Heuristics for the re-balancing of a vehicle assembly line

This article deals with a re-balancing problem which is the object of an industrial collaboration with a French automotive firm. The constraints of the problem are composed of basic constraints from line balancing problems and of specific constraints such as working height and storage area length constraints. To solve the problem, we propose three heuristics based on operation transfers in order to obtain a feasible balancing or to improve it. The considered objectives are the minimisation of the number of stations, then the load smoothing while transfering a minimum number of operations. The objectives are independently considered.

DaimlerChrysler installs new robot‐based flexible assembly line

PurposeThis paper seeks to describe a new flexible, robot‐based welding line, installed at an American DaimlerChrysler vehicle assembly plant.Design/methodology/approachThis paper first considers the motivations behind flexible manufacturing strategies (FMSs) and then describes a system installed at the Sterling Heights DaimlerChrysler plant.FindingsThis paper shows that the adoption of robot‐based flexible assembly allows different models and model variants to be assembled on a single line, yielding operational, commercial and financial benefits.Originality/valueThis paper illustrates the value of adopting an FMS at a vehicle assembly line.

블록 보간법을 이용한 산업용 로봇의 3차원 위치 보정기법

This paper proposes a self-calibration method of robots those are used in industrial assembly lines. The proposed method is a position compensation using laser sensor and vision camera. Because the laser sensor is cross type laser sensor which can scan a horizontal and vertical line, it is efficient way to detect a feature of vehicle and winding shape of vehicle's body. For position compensation of 3-Dimensional axis, we applied block interpolation method. For selecting feature point, pattern matching method is used and 3-D position is selected by Euclidean distance mapping between 462 feature values and evaluated feature point. In order to evaluate the proposed algorithm, experiments are performed in real industrial vehicle assembly line. In results, robot's working point can be displayed 3-D points. These points are used to diagnosis error of position and reselecting working point.

Fumes-to-fuel system turns Ford’s waste paint exhaust into power

Ford Motor Company and Detroit Edison have jointly developed a new ‘Fumes-to-Fuel’ System that, instead of incinerating paint fumes from a vehicle assembly line, turns them into hydrogen that can be used in fuel cells. The new system has been patented by Detroit Edison in the US, and internationally by Ford and Edison. This is a short news story only. Visit www.re-focus.net for the latest renewable energy industry news

Fire protection pumps installed at Jaguar production plant

A new range of fire protection pumps and associated equipment has been installed at Jaguar Car’s Halewood production facility in the UK, where the prestigious new Jaguar X-Type car is manufactured. The fire pumps were selected because they enable prompt, reliable and effective fire control in the facility’s vehicle trim and assembly line, which processes up to 100,000 vehicles a year.