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In a kitting supply system, the occurrence of material-handling errors is unavoidable and will cause serious production losses to an assembly line. To minimize production losses, this paper aims to present a dynamic scheduling problem of automotive assembly line considering material-handling mistakes by integrating abnormal disturbance into the material distribution problem of mixed-model assembly lines (MMALs).

A multi-phase dynamic scheduling (MPDS) algorithm is proposed based on the characteristics and properties of the dynamic scheduling problem. In the first phase, the static material distribution scheduling problem is decomposed into three optimization sub-problems, and the dynamic programming algorithm is used to jointly optimize the sub-problems to obtain the optimal initial scheduling plan. In the second phase, a two-stage rescheduling algorithm incorporating removing rules and adding rules was designed according to the status update mechanism of material demand and multi-load AGVs.

Through comparative experiments with the periodic distribution strategy (PD) and the direct insertion method (DI), the superiority of the proposed dynamic scheduling strategy and algorithm is verified.

To the best of the authors’ knowledge, this study is the first to consider the impact of material-handling errors on the material distribution scheduling problem when using a kitting strategy. By designing an MPDS algorithm, this paper aims to maximize the absorption of the disturbance caused by material-handling errors and reduce the production losses of the assembly line as well as the total cost of the material transportation.

The purpose of this paper is to develop a quantitative model to assess probability of errors and errors correction costs in parts feeding systems for assembly lines.

Event trees are adopted to model errors in the picking-handling-delivery-utilization of materials containers from the warehouse to assembly stations. Error probabilities and quality costs functions are developed to compare alternative feeding policies including kitting, line stocking and just-in-time delivery. A numerical case study is included.

This paper confirms with quantitative evidence the economic relevance of logistic errors (LEs) in parts feeding processes, a problem neglected in the existing literature. It also points out the most frequent or relevant error types and identifies specific corrective measures.

While the model is general purpose, conclusions are specific to each applicative case and are not generalizable, and some modifications may be required to adapt it to specific industrial cases. When no experimental data are available, human error analysis should be used to estimate event probabilities based on underlying modes and causes of human error.

Production managers are given a quantitative decision tool to assess errors probability and errors correction costs in assembly lines parts feeding systems. This allows better comparing of alternative parts feeding policies and identifying corrective measures.

This is the first paper to develop quantitative models for estimating LEs and related quality cost, allowing a comparison between alternative parts feeding policies.

Driven by sustainable production, mobile robots are introduced as a new clean-energy material handling tool for mixed-model assembly lines (MMALs), which reduces energy consumption and lineside inventory of workstations (LSI). Nevertheless, the previous part feeding scheduling method was designed for conventional material handling tools without considering the flexible spatial layout of the robotic mobile fulfillment system (RMFS). To fill this gap, this paper focuses on a greening mobile robot part feeding scheduling problem with Just-In-Time (JIT) considerations, where the layout and number of pods can be adjusted.

A novel hybrid-load pod (HL-pod) and mobile robot are proposed to carry out part feeding tasks between material supermarkets and assembly lines. A bi-objective mixed-integer programming model is formulated to minimize both total energy consumption and LSI, aligning with environmental and sustainable JIT goals. Due to the NP-hard nature of the proposed problem, a chaotic differential evolution algorithm for multi-objective optimization based on iterated local search (CDEMIL) algorithm is presented. The effectiveness of the proposed algorithm is verified by dealing with the HL-pod-based greening part feeding scheduling problem in different problem scales and compared to two benchmark algorithms. Managerial insights analyses are conducted to implement the HL-pod strategy.

The CDEMIL algorithm's ability to produce Pareto fronts for different problem scales confirms its effectiveness and feasibility. Computational results show that the proposed algorithm outperforms the other two compared algorithms regarding solution quality and convergence speed. Additionally, the results indicate that the HL-pod performs better than adopting a single type of pod.

This study proposes an innovative solution to the scheduling problem for efficient JIT part feeding using RMFS and HL-pods in automobile MMALs. It considers both the layout and number of pods, ensuring a sustainable and environmental-friendly approach to production.

Waste minimization strategies and the relative significance of construction waste sources were examined using a survey of 24 construction firms operating in Australia. The results indicated that a sizeable proportion of respondent firms did not have specific policies for minimizing waste. Furthermore, while a majority of firms with specific waste minimization policies made efforts to minimize waste at source, i.e. to avoid generating waste in the first place, this minimization was limited to waste generated by site offices and amenities. Potential scope exists for improving the effectiveness of waste minimization at source by addressing the sources of all waste generated during the construction phase. The survey results indicated that the five most significant sources of construction waste were design changes, leftover material scraps, wastes from packaging and non‐reclaimable consumables, design/detailing errors, and poor weather. Potential opportunities for minimizing the amount of waste generated on construction project sites are identified.

To present ways for empowering contractors in improving environmental performance particularly to meet the requirements defined in ISO 14000.

To review the traditional methodologies for protecting the environment in undertaking construction activities, investigate the limitations of these methods and the associated reasons, and apply the principles of ISO 14000 environmental management system (EMS) to develop an effective framework for helping contractors to become competent in implementing environmental management.

The major methodologies developed for protecting the environment in construction include governmental regulations, economic measures, and EMSs. However, the applications of these measures are limited. The typical causes contributing to the limitation include the clash between cost and environment, environmentally passive culture within construction industry, lack of cooperation among project parties, and clash between contract time and implementing environmental management methods. Furthermore, the practice of environment management is mainly driven by external impetus such as legal enforcement incentive programmes from government. However, the effectiveness cannot be gained if internal motivation does not exist. This paper introduces a framework to help a contractor to cultivate an environmentally friendly culture within its organization.

This paper proposes a framework for empowering contractors in improving environmental performance by identifying the weaknesses of the existing practice and applying a systematic approach of implementing environmental management approaches.

Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

The purpose of this paper is to review the fundamental concept of supply chain management (SCM) and discusses the facts that a road to success in the process of design, development, implementation and operation of a supply chain (SC) is the identification of superior strategies and clear objectives. To understand important SC strategies for a complete success, main strategies need to be identified. The literature of SC is filled with a wide range of strategies applied successfully across various enterprises that reviewed briefly in this paper.

The paper provides key strategies of SCM, and discusses the fact that the vision for the excellent SCM can be built on principles as such as speed, quality, cost, flexibility, quality leadership, customer focused, collaboration, and integrated information system.

To make the excellent SCM successful, management must be committed to high standard of performance including competitive lead times to customers, significantly reduced inventories, world‐class product quality, and reduced process and product complexity.

Because a better management of production system is related to the full understanding of the technologies implemented and the system under consideration, the excellent SCM system including its three As are discussed and metrics used to measure performance are elaborated.

Flexible materials are used extensively in a wide range of industrial applications including the manufacture and assembly of garment and footwear products, the packaging industry and aircraft manufacturing. These applications are often extremely labour intensive requiring fast and accurate manipulation of materials by skilled human operators. This has resulted in numerous international research and development efforts to automate certain handling and manipulation processes involving flexible materials. Much of the research has been inspired by real industrial problems, and thus has been mainly sponsored by industry. A variety of innovative techniques and methods have emerged either addressing specific industrial problems, or suggesting a number of generic solutions. This paper closely examines the international research effort of automatic manipulation of flexible materials through a classification of workpieces in terms of their broad geometric shape, industrial applications, and individual processes.

In the garment industry, web lace fabric material must be tensioned and placed at the right position and orientation prior to the cutting process. In order to avoid a bottleneck, the speed of material handling must be relatively fast compared to the laser cutting speed so that the use of a laser for rapid prototyping of two‐dimensional (2D) cutting shapes is feasible. The purpose of this paper is to describe the development of a novel gripping system for handling flexible web materials.

The manner in which this intelligent material handling system operates will be discussed in this paper. This includes its system configuration, errors that may occur during the web handling operation, and sequential operations of web distortion control. The material handling system uses a machine vision system coupled with a self‐tuning motion control strategy to assist the material handling system in controlling the web tension, adjusting the web deformation parameters and transporting the web materials.

The online image analysis and a novel mechanical design concept, coupled with the motion controller, are the key issues in the mechatronic integration of this intelligent web‐based material handling system.

The paper presents a novel approach to designing and realizing an intelligent gripping system, which has not previously been attempted.

This paper aims to examine the structure of the control strategy that is being deployed on the control of the mobile materials handling platform, from the higher level onboard interface software to the low‐level control system that is tasked with the dynamic stability of the platform.

The application of the principle of the inverted pendulum in mobile robotics has only recently been made possible by advances in the technology of electronics. A mobile materials handling platform has been designed and built for use in manufacturing systems of the future. The principle of the inverted pendulum has been incorporated into the design. This means that the platform is able to maintain dynamic stability during specific periods of operation. The mechatronic engineering approach was adopted in the design of the platform, which produced an integrated embedded system.

Open source software being implemented onboard the platform for interfacing between the platform and remote client computers is found to be easily customisable according to the requirements of one's application. A solution to the problem of nonholonomic motion constraints that concern any differential drive mobile robot was found in a nonlinear state transformation algorithm. The algorithm was implemented on an intermediate level between the interface software and the low‐level control system. The low‐level feedback control system was designed using a linear quadratic regulator design method. Simulations of this control system showed that it was robust enough to reject predetermined disturbances in system characteristics.

The application of a mobile platform specifically designed for materials handling based on the principle of the inverted pendulum has not been attempted to date.