Automotive Manufacturing System Research Articles

Implementing Zero Impact Factories in Volkswagen’s Global Automotive Manufacturing System: A Discussion of Opportunities and Challenges from Integrating Current Science into Strategic Management

The current exceeding of six out of nine planetary boundaries requires a significant transition of human societies towards absolute sustainability. Industrial manufacturing systems were and still are an important motor for socio-economic development but at the cost of a significant negative impact on the biosphere. Current concepts in absolute sustainability and sustainable manufacturing provide solutions for sustainability transitions in industry, but various methodological, technical and procedural challenges arise during their adaptation in industrial practice. The development and operationalization of a “zero impact factory” strategy by Volkswagen Group has identified various implementational challenges, which are discussed in this article. First, an overview of motivations for “zero impact” transformations in industry are pointed out. Second, relevant aspects for the strategic management of sustainability transitions in manufacturing companies are highlighted based on a literature analysis. Third, the strategy development process is explained based on a systematic structure, which includes design-thinking principles for sustainability transitions of large technical systems such as factories in global manufacturing systems. Fourth, the developed strategy content is presented, including (1) the strategy vision, (2) the defined quantified “zero impact” goals, (3) a system model and a prototype of a zero impact factory, (4) the developed “Impact Points” and the “Site Checklist” methods (for evaluating the environmental transformation of a factory) and (5) the definition of processes for strategic management during strategy operationalization. Finally, various organizational challenges and opportunities are pointed out, which are considered novel insights from industrial practice and relevant for the science-based strategic management within automotive companies and other global industrial manufacturing organizations, as well for advancing sustainability concepts in applied industrial science.

Scheduling analysis of automotive glass manufacturing systems subject to sequence-independent setup time, no-idle machines, and permissive maximum total tardiness constraint

With the increasing demand for automotive glass, improving the efficiency of automotive glass manufacturing systems can make full use of production resources and reduce the waste of natural and social resources. Therefore, this work aims to provide an efficient method for a real-world two-stage hybrid flow shop scheduling problem with small batches in an automotive glass manufacturing system. For the investigated problem, there is a significant setup time at the first stage, the second stage is served by machines that should not be interrupted, and each batch has a due date. Such constraints make this scheduling problem challenging. To solve this problem, a mixed integer linear programming model is established. Also, two properties and three theorems are given to enhance the problem-solving process. Subsequently, an efficient genetic algorithm is carefully designed to solve large-scale problems by considering the properties of the system. Meanwhile, an improvement scheme is proposed to decrease the running time of the algorithm, and experimental results show that this scheme can reduce the running time by 280 s at most from the average results of different scale problems. Finally, extensive experiments are carried out and a real-world case is solved to demonstrate the efficiency and effectiveness of the designed genetic algorithm. Also, the Taguchi method is adopted to tune the parameters for the designed algorithm.

Optimizing Automotive Manufacturing Systems through TOGAF Modelling

The objective of this research is to examine the viability of implementing the Open Group Architecture Framework to enhance the efficiency and performance of automotive manufacturing systems. The automotive industry remains confronted with challenges pertaining to the enhancement of manufacturing processes, the reduction of product development time, and the adjustment to swift technological progressions. The primary obstacles encountered in implementing process innovation, the complexity of the IT infrastructure, and the absence of system integration constitute the most significant challenges. The primary aim of this study is to present a resolution through the application of the TOGAF framework. By implementing this strategy, system synchronization will be enhanced, IT infrastructure will be simplified, and process innovation will be able to respond to market fluctuations more rapidly. The existing business processes are streamlined and consistent with the strategic progress of vehicle manufacturing firms. Nonetheless, business processes involving architectural applications continue to diverge from market demands and fail to align with evolving business requirements. In the context of automotive manufacturing, the TOGAF modeling methodology will be applied to analyze the data architecture, application architecture, strategic elements, and information technology infrastructure. Advise stakeholders in the automotive industry, facilitating the integration of TOGAF principles into endeavors to redesign systems. This will reduce the attainment of innovation, adaptability, and efficiency, all of which are critical for sustaining competitiveness in a dynamic marketplace. By applying TOGAF principles to the automotive manufacturing system, Enterprise Architecture can support ever more complex business requirements.

Efficient Energy Use in Manufacturing Systems—Modeling, Assessment, and Management Strategy

Currently, studies on the energy efficiency of manufacturing systems usually lack synthetic and systematic techniques. In this paper, a holistic framework is demonstrated in order to achieve more sustainable manufacturing, which covers machine-level, system-level and life-cycle-level energy efficiency techniques. Based on these, the mechanism of how energy consumption is affected by machining processes and system operation is analyzed to achieve a comprehensive decision on energy efficiency optimization. Four main topics are included in this paper: (1) Hierarchical sustainability goals and metrics for energy-efficient manufacturing; (2) Machine-level machining processes optimization for energy efficiency enhancement; (3) System-level innovations for efficient consumption management; (4) Life-cycle level energy flow modeling and energy recycling strategy. An automotive engine manufacturing system is taken as an example to build a concrete understanding of the application of the framework. Moreover, this holistic framework establishes the theoretical basis for promoting the energy efficiency of automotive engine manufacturing systems. Furthermore, the proposed techniques can provide decision-making support for achieving sustainable manufacturing in a wider scope of mechanical manufacturing.

Maintenance policy optimization for buffered serial systems considering energy-saving based on dual time windows

This paper proposes a novel optimal maintenance policy considering energy-saving based on dual time windows is proposed for a serial production system with limited buffering. The machines suffer from degradation, and the degradation process obeys the Gamma random process. Based on the dual time windows, condition-based preventive maintenance and opportunistic maintenance are activated: when a machine reaches a set state (i.e., threshold deterioration state), the preventive maintenance action is taken, and the time of preventive maintenance performed is determined by the time window w; meanwhile, the time window W is used to determine whether the other machines need opportunity maintenance. To reduce energy consumption, and increase the proportion of effective energy in the manufacturing process, the energy-saving time window is used to find the energy-saving opportunities for the system. The impact of different maintenance thresholds and dual time windows on the maintenance cost per effective product is discussed through Monte Carlo simulation. A practical example of an automotive manufacturing system is provided, and comparative analyses with other maintenance policies are used to illustrate the superiority of the proposed policy in energy saving, cost reduction, and quality improvement.

Manufacturing System Design Decomposition: An Ontology for Data Analytics and System Design Evaluation

This paper builds on prior research to develop the Manufacturing System Design Decomposition (MSDD) from the perspective that it may serve as an ontology for evaluating the efficacy of manufacturing system design and implementation. Common ontology processes and formats were compared and contrasted to Axiomatic Design. The MSDD concept was translated into Web Ontology Language (OWL) and an XML format for comparison. An application in Automotive manufacturing system design was discussed from the Architecture Viewpoint of Ontology.

Determining failure distributions for robust simulation model in assembly line of automotive body shop

Simulation technology is the most popular and powerful tool for analyzing complex system such as automotive manufacturing system. However, sufficient

Petri net based decision system modeling in real-time scheduling and control of flexible automotive manufacturing systems

This paper presents the design and the implementation of a Petri net (PN) model for the control of a flexible manufacturing system (FMS). A flexible automotive manufacturing system used in this environment enables quick cell configuration, and the efficient operation of cells. In this paper, we attempt to propose a flexible automotive manufacturing approach for modeling and analysis of shop floor scheduling problem of FMSs using high-level PNs. Since PNs have emerged as the principal performance modeling tools for FMS, this paper provides an object-oriented Petri nets (OOPNs) approach to performance modeling and to implement efficient production control. In this study, we modeled the system as a timed marked graph (TMG), a well-known subclass of PNs, and we showed that the problem of performance evaluation can be reduced to a simple linear programming (LP) problem with m−n+1 variables and n constraints, where m and n represent the number of places and transitions in the marked graph, respectively. The presented PN based method is illustrated by modeling a real-time scheduling and control for flexible automotive manufacturing system (FAMS) in Valeo Turkey.

Study on Intelligent Reconfigurable Automobile Manufacturing System Model

An intelligent reconfigurability model based on multi-agent theory was proposed in this paper to improve feasibility of automotive manufacturing system. Each production management department in automobile manufacturing enterprises was designed as an independent agent. The practicability and rationality of the manufacturing system model was simulated as communication and interactive between different agents in this multi-agent system through JAFMAS. The application of multi-agent model in the design of automobile manufacturing system can promote the reconfigurability and intelligent level of the system.

The development of a hybrid knowledge-based system for the design of a Low Volume Automotive Manufacturing (LVAM) system

A conceptual design approach is an important stage for the development of a hybrid Knowledge-Based System (KBS) for Low Volume Automotive Manufacturing (LVAM). The development of a hybrid KBS, which is a blend of KBS and Gauging Absences of Pre-requisites (GAP), is proposed for LVAM research. The hybrid KB/GAP system identifies all potential elements of LVAM issues throughout the development of this system. The KBS used in the system design stage of the LVAM system analyses the gap between the existing and the benchmark organisations for an effective implementation through the GAP analysis technique. The proposed KBLVAM model at the design stage explores three major components, namely LVAM car body parts manufacturing perspective, LVAM competitive priorities perspective and LVAM lean environment perspective. Initial results reveal that the KBLVAM system has identified, for each perspective modules and sub-modules, the Problem Categories (PC) in a prioritised manner.

A simulation study integrated with analytic hierarchy process (AHP) in an automotive manufacturing system

A variety of circumstances, such as developing a new product, changing the design of an existing product, changing the production volume, or changing the product mix, can drive the need for a manufacturing system redesign. Simulation technology has been widely used for evaluating manufacturing system design alternatives. Various performance measures including throughput, utilization of resources, lead-time, and work in process are obtained from simulation studies. However, the dimensions of performance measures are different, and it requires that the trade-offs between them should be considered. In addition, personal preferences in the selection of performance measures vary from person to person. Thus, the multi-criteria decision-making (MCDM) system is required to complement the simulation technology. This paper presents a case study that integrates a simulation study with analytic hierarchy process (AHP), applied to the design of a transmission case line in a Korean automotive factory. The simulation model is developed with QUEST®. Four performance measures (criteria) and seven design alternatives are considered utilizing AHP.

Five crisp and fuzzy models for supply chain of an automotive manufacturing system

Supply Chain Management (SCM) is a new approach to production planning. It integrates the components of supply chain in a holistic manner. Modeling this large-scale system, which contains all effective enterprises in production such as raw material suppliers, part manufacturers, assembly plants, distribution organizations, and the like, is challenging for managers, engineers and researchers. This paper concentrates on supply chain system modeling with fuzzy linear programming, and fuzzy expert system for an automobile plant. First, a linear programming model is developed in such a way that while the input data is fuzzy, the constraints are crisp. In the second linear model, the coefficients of the model are crisp while the constraints are fuzzy. In the third model, we aggregate the first and the second models into one fuzzy linear programming where all constraints and coefficients are fuzzy. In each case, we compare the results with those of classical SC models. Finally, a rule based fuzzy expert system for SC is developed and the results are compared with those of the classical and fuzzy LP models. The results of the fuzzy expert system show its superiority over the former crisp and fuzzy linear programming models.

Ergonomic Optimization of a Manufacturing System Work Cell in a Virtual Environment

The paper deals with the development of a methodology for studying, in a virtual environment, the ergonomics of a work cell in an automotive manufacturing system. The methodology is based on the use of digital human models and virtual reality techniques in order to simulate, in a virtual environment, human performances during the execution of assembly operations. The objective is to define the optimum combination of those geometry features that influence human postures during assembly operation in a work cell. In the demanding global marketplace, ensuring that human factors are comprehensively addressed is becoming an increasingly important aspect of design. Manufacturers have to design work cells that conform to all relevant Health and Safety standards. The proposed methodology can assist the designer to evaluate the performance of workers in a workplace before it has been realized. The paper presents an analysis of a case study proposed by COMAU, a global supplier of industrial automation systems for the automotive manufacturing sector and a global provider of full maintenance services. The study and all the virtual simulations have been carried out in the Virtual Reality Laboratory of the Competence Regional Center for the qualification of transportation systems (CRdC “Trasporti” - www.centrodicompetenzatrasporti.unina. it), which was founded by the Campania region with the aim of delivering advanced services and introducing new technologies into local companies operating in the field of transport.

Using simulation to predict system performance: a case study of an electro‐phoretic deposition plant

Describes a computer simulation technique which has been applied to model an automotive manufacturing system in order to predict the system performance under an increasing demand. Using Sim View, a locally developed, graphically animated simulation package, the electro‐phoretic deposition plant was modelled and sensitivity analysis was carried out. Confirms some of the problems that were thought may arise, and highlights some other issues that may become problematic. Aims to produce possible suggestions for avoiding problems and improving the performance of the system. Plans further uses of the simulation model in studies to gain greater efficiency in the system and possibly to experiment with any future upgrades that may be considered.