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The purpose of this paper is to present a literature review on parts feeding policies and to provide the components of parts feeding systems via a classification structure.

This paper determines the scope and components of parts feeding systems via a classification structure under three main components such as the storage of parts, transport of parts and feeding policy. Afterward, it is focused on parts feeding policies and the related papers are reviewed and analyzed according to their feeding policy types, objectives, solution methodologies and the application types.

A classification structure showing the components and scope of parts feeding systems is provided. Parts feeding policies are handled in detail and feeding policy types, objectives, solution methodologies and application types in the existing studies are presented in this paper. However, the paper highlights the open research areas and advances for academics and presents applied solution methodologies and case studies for practitioners.

This paper reveals the scope of parts feeding systems by presenting a classification structure including three main components and related subcomponents and provides a comprehensive literature review on parts feeding policies.

This paper aims to focus on the novel design and development of an automatic feeding system which is capable of feeding cylindrical parts which are fragile and powdery in nature and possess asymmetrical features such as a groove near to one end.

It is an active feeder, performing its task without having to reject any feeding part by performing active orientation of feeding parts that are in the undesired orientation. This design incorporating active orientating capability is aimed at 100 percent feeding efficiency. The system is controlled and driven by a programmable logic controller and electropneumatics.

System evaluation results showed that the average jam rate is below 5 percent and the percentage of correctly orientated parts is above 95 percent. With enhancement and fine tuning, the system could become a very useful feeder for industry in the future.

The scope of this paper focuses on presentation of the design concept, development and evaluation of the feeder only and design calculations are not included.

This paper is of value to those who are involved in the manufacturing of small delicate and powdery engineering parts such as those providing performs to the semiconductor industry for encapsulation of integrated circuit chips.

The purpose of this paper is to cut down energy consumption and eliminate production waste on mixed-model assembly lines. Therefore, a supermarket integrated dynamic cyclic kitting system with the application of electric vehicles (EVs) is introduced. The system resorts to just-in-time (JIT) and segmented sub-line assignment strategies, with the objectives of minimizing line-side inventory and energy consumption.

Hybrid opposition-based learning and variable neighborhood search (HOVMQPSO), a multi-objective meta-heuristics algorithm based on quantum particle swarm optimization is proposed, which hybridizes opposition-based learning methodology as well as a variable neighborhood search mechanism. Such algorithm extends the search space and is capable of obtaining more high-quality solutions.

Computational experiments demonstrated the outstanding performance of HOVQMPSO in solving the proposed part-feeding problem over the two benchmark algorithms non-dominated sorting genetic algorithm-II and quantum-behaved multi-objective particle swarm optimization. Additionally, using modified real-life assembly data, case studies are carried out, which imply HOVQMPSO of having good stability and great competitiveness in scheduling problems.

The feeding problem is based on static settings in a stable manufacturing system with determined material requirements, without considering the occurrence of uncertain incidents. Current study contributes to assembly line feeding with EV assignment and could be modified to allow cooperation between EVs.

The dynamic cyclic kitting problem with sub-line assignment applying EVs and supermarkets is solved by an innovative HOVMQPSO, providing both novel part-feeding strategy and effective intelligent algorithm for industrial engineering.

This paper aims to propose a combined methodology to help decision makers in evaluating and selecting the most effective part feeding system.

As a first step of the methodology, a hierarchical clustering analysis is applied to design a kitting or hybrid feeding system. Second, activity-based costing methodology is applied to determine which system is better according to their costs. Besides, sensitivity analysis is implemented to observe the behavior of the system in case of the takt time changes.

Using kitting systems purely can lead to problems because of the big and expensive parts in the mixed-model assembly systems. Therefore, the hybrid feeding policy can provide better solutions for such systems.

A case study is conducted in a company and the most produced product of the company is considered to design the part feeding system. Results indicated that transportation cost has a large proportion on the total cost and the hybrid feeding policy may be a good solution to reduce this cost.

The paper includes implications for the design of hybrid feeding systems in lean-based assembly lines. The proposed methodology may be a practical tool for decision makers to design and decide on the part feeding policy.

Kitting design has not been studied yet to the best of the authors’ knowledge. Besides, there is no certain decision methodology indicating which system is better. In this study, different methods are combined as a new methodology with the purpose of industrial decision-making.

The paper describes analyses which have been developed to determine the cost of assembly using a multi‐arm assembly robot fed by a wide variety of different feeding systems and for a wide range of product styles, mixes, and batch sizes.

Outlines development work on the surfing hopper, a new parts feeding system where chain conveyors with free rollers are driven by a variable‐speed motor and a flexible belt is pushed up partly by the free rollers to generate a wave in the belt. Describes how the wave effect keeps the stacked parts level and how experiments were carried out using different parts materials such as small water‐filled bottles and nuts made of steel. Looks at studies carried out on feeding correctly orientated parts to the assembly station and experiments on surfing feeding system with regard to part separation on the belt. Concludes that the surfing hopper can supply heavy parts intermittently at a rough definite supply ratio, without jamming and entangling the parts and without damage to the belt.

The paper aims to focus on in-house part logistics design and management for assembly systems in which supermarket storage is adopted and coupled with an automated transportation system. In this context, this work aims to assess the transportation mode selection problem to speed up the preliminary design phase.

The paper is divided into two main parts. The first one provides and discusses a new conceptual framework derived from the authors’ experience in the field and from previous published works. The framework aims to support managers in problem comprehension by setting three problem sub-phases, key input parameters and qualitative guidelines without losing sight of the big picture. The second part focuses on the transportation mode selection sub-phase by assessing an analytical study followed by a multi-scenario analysis.

The final outcome of this work is a decision support matrix capable of setting technical guidelines that are helpful to managers and practitioners to speed up the transportation mode selection problem in the preliminary phases.

This work is beneficial for supporting managers in understanding the main decisional steps involved in the design of a part-feeding system with a supermarket by discussing the three problem sub-phases and key input parameters and providing both qualitative and quantitative guidelines. Moreover, this study explores the transportation mode selection problem, which is not yet largely explored in the published literature.

This paper describes a manipulation primitive called toppling – knocking a part over. We derive the mechanical conditions for toppling and describe two applications to conveyor‐based feeding. Toppling complements previous approaches to conveyor‐plane feeding, allowing full three‐dimensional parts feeding on a constant‐speed conveyor.

Flexible feeding is an emerging alternative to traditional part feeding methods. This alternative greatly enhances the versatility of a manufacturing workcell by using a robot manipulator and sophisticated sensing devices such as machine vision, thereby significantly reducing both cost and set up time. This article explores the benefits of a new model in PC‐based robot control, which makes the development of flexible feeders and similar applications much easier than using traditional robot programming environments. It also explores how a programming paradigm based on a well‐defined model of the workcell greatly simplifies both the logic of the application and the calibration of the physical machine.

This paper aims to investigate the part feeding scheduling problem with electric vehicles (EVs) for automotive assembly lines. A point-to-point part feeding model has been formulated to minimize the number of EVs and the maximum handling time by specifying the EVs and sequence of all the delivery tasks.

First, a mathematical programming model of point-to-point part feeding scheduling problem (PTPPFSP) with EVs is presented. Because the PTPPFSP is NP-hard, an improved multi-objective cuckoo search (IMCS) algorithm is developed with novel search strategies, possessing the self-adaptive Levy flights, the Gaussian mutation and elite selection strategy to strengthen the algorithm’s optimization performance. In addition, two local search operators are designed for deep optimization. The effectiveness of the IMCS algorithm is verified by dealing with the PTPPFSP in different problem scales.

Numerical experiments are used to demonstrate how the IMCS algorithm serves as an efficient method to solve the PTPPFSP with EVs. The effectiveness and feasibility of the IMCS algorithm are validated by approximate Pareto fronts obtained from the instances of different problem scales. The computational results show that the IMCS algorithm can achieve better performance than the other high-performing algorithms in terms of solution quality, convergence and diversity.

This study is applicable without regard to the breakdown of EVs. The current research contributes to the scheduling of in-plant logistics for automotive assembly lines, and it could be modified to cope with similar part feeding scheduling problems characterized by just-in-time (JIT) delivery.

Both limited electricity capacity and no earliness and tardiness constraints are considered, and the scheduling problem is solved satisfactorily and innovatively for an efficient JIT part feeding with EVs applied to in-plant logistics.