Improvement in planning and resource management for an automotive company’s parts feeding system

The increasing sophistication of the automotive market and the constant change in customer requirements increases companies’ concern to ensure efficient internal logistic flows in line with Just-In-Time philosophy and Lean principles, to deal with wastes and variability. Variability arises from the growing differentiation of products, from the adoption of multi and mixed model assembly lines, and from the uncertainty in customer demand resulting from the worldwide outbreak of COVID-19. Considering the automotive supplier company as research subject, several problems were found to be compromising the efficiency of one of its in-plant parts’ feeding systems, the most critical problem being the lack of planning and management of resources (human and material) needed to perform the logistic service. Through Action-Research methodology stages, the actions taken culminated in the development of a simulation and decision-support tool for the component supply system resource management and efficiency improvement. The simulations made revealed reliable and adjusted results of workload and workforce to face the variations in customer demand and the existing product mix. After the tool creation, resource planning and balancing was no longer based on managers experience and empirical knowledge only but based on scientific knowledge: concise and reliable data from information systems, measurements, study of times, and literature review on in-plant milk run systems, lean, just-in-time and continuous improvement techniques.info:eu-repo/semantics/publishedVersio

A study of a kanban based assembly line feeding system through integration of simulation and particle swarm optimization

With increase in differentiation and decreasing batch size of products, feeding the assembly line at regular intervals is considered to be a critical problem in today's manufacturing sector. Yet no clear solution has been developed for this problem; therefore, the main focus of this research is to discuss the different aspects of line feeding, the latest trend in literature, and to propose an innovative method to support solving the problem. A discrete event simulation model is developed and a mathematical model based on particle swarm optimization is used to support the simulation. The hybrid model is finally applied to practical situations. Results show how different settings of kanban influence the performance of the assembly line feeding system. The biggest novelty item is certainly the recognition of the trade-off between kanban size and number of kanban and the importance of investigating its behaviour during the design of the system. (C) 2019 by the authors; licensee Growing Science, Canad

Normalizing and Procurement optimization with Supermarket and Asset monitoring

Automobile part suppliers have struggled hard in the past to meet the requirements of the manufacturing companies. The Original Equipment Manufacturers (OEM) are constantly facing demand changes from the customer end. The connected world has raised the expectation of customers to provide cost efficient yet quality automobiles. Part suppliers are stressed to deliver the products in Just-In-Time (JIT) sequence to reduce the bulk stock in the warehouses. The thesis revolves around the review of JIT models in the automobile assembly process. It specially focuses on the importance of supermarket and their uses in providing the parts through tow train scheduling and routing. The models which are already existing are revised by changing certain criteria and combining all the models published into one system to make it easy for the readers to understand. The purpose of the model normalization is to have visibility on quantity of parts needed in supermarket. This is achieved by the normalized routing and scheduling models which exactly tells when, where and the number of parts transported to the desired work floor at specific time just before assembling. This gives the number of parts being used from the supermarket. From this the number of parts needed on the supermarket and subsequently to the warehouse are calculated. The second half of the thesis focuses on procurement optimization after the revised demand of inventory in the warehouse. Procurement optimization paves way for choosing the right supplier according to the volatility in demand. The second half of the thesis discusses about the advantages of super market installation on supplier selection by doing procurement optimization using Mixed Integer Linear Programing. To end the re-search work on the automobile assembly process, the current problems faced by the industry and especially by the suppliers are discussed. A new way to mitigate the supplier loss is discussed with the introduction of Internet of Things (IoT) based solutions by tracking the assets. Asset monitoring devices have been gaining attention worldwide to safely transport the goods without damage. Transparency and visibility is provided in the form of bidirectional gateway process by the wireless asset monitoring devices. Not only the suppliers but also the OEMs are benefitted as it supports the JIT process and faster assembly of the automobiles with less number of damages

Simulation Optimization Studies of Routing and Process Flow Problems

Computer aided simulation is emerging as a powerful tool for numerical analysis and in conducting performance evaluations of complex systems that depend on a multitude of variables. The primary objective in such simulation studies is to gauge the performance of the system under a various constraints and operating conditions. The effects of changing the operating parameter space can thus be analyzed without having to implement costly changes. Simulations are also carried out for the baseline scenarios to verity and validate the basic underlying system model. In this thesis research, two practical problems were studied through numerical modeling, and optimized solutions obtained for both. Optimizing the pick-up and delivery routes using a commercial software tool was the first task. Optimization of a production assembly line using a discrete event simulation tool was the second project that was carried out. The primary objective for the first task was to explore various routing scenarios and determine delivery routes that would minimize the total network mileage, while maintaining the pick-up time slots requested by the clients. A related task was to evaluate the possible advantages of centralizing all routing activity from a single site, instead of the two-hub scenario currently in effect. A total of eight different scenarios were studied as part of this effort. The second task involved optimization of the throughput of a fuel injector plant by placing buffers within the assembly lines for increased productivity

Improving efficiency of material flows in an automotive assembly plant:A case study

This paper investigates the in-plant logistics processes in automotive manufacturing and specifically, the material flows between the storage facility, the production lines, and the internal returns area. The aim is to improve the efficiency of the plant by looking at the current material flows of the case study company. Qualitative and quantitative data was collected through interviews and personal observations and was analysed. Using discrete event-based simulation, the current material flows were investigated. Our analysis showed that in plant's internal returns area efficiency gains are possible by reducing traffic congestion. A solution with minor changes in the layout was proposed and tested which showed an increase in the capacity of the system and a reduction in delays