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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.

Electrostatic precipitators (ESP) and fabric filters (FF) are the main air pollution control equipment utilized to clean dust laden fumes from utility boilers. The choice among these systems depends on specific site conditions such as dust characteristics, required efficiency, gas flowrate and temperature. ESP are generally characterized by higher capital investments and lower operating charges, while the opposite may be said for FF baghouses. As a consequence, ESP present higher total costs when high specific collection areas are required, as happens in the case of low‐sulfur high‐resistivity dust. However, significant reductions in both capital investment and operating charges may be obtained with pulsed energization of precipitators working in severe back corona conditions. This possibility greatly enlarges the field of applications in which ESP are a lower cost option compared to fabric filters. In the paper an economic comparison of pulse energized ESP, with conventional ESP, reverse‐air, shaker, and pulse‐jet baghouses is performed. A mapping of the operating conditions in which the adoption of each examined control technology is economically convenient is also defined.

The purpose of this paper is to develop an optimization model allowing the choice of parts feeding policy to assembly lines in order to minimize total cost.

An integer linear programming mathematical model is developed to assign the optimal material feeding policy to each part type. The model allows choice between kitting, line stocking and just in time delivery policies.

The choice of assembly lines feeding policy is not trivial and requires a thorough economic comparison of alternatives. It is found that a proper mix of parts feeding policies may be better that adopting a single material delivery policy for all parts.

The model is aimed at single-model assembly lines operating in a deterministic environment, but can be extended to the multi-model line case. While relevant quantitative cost drivers are included, some context-related qualitative factors are not included yet. The model assumes that information about product structure and part requirements are known and that a preliminary design of the assembly system has been carried out.

Production managers are given a quantitative-decision tool to determine the optimal mix of material supply policies at an early decision stage.

Respect previous simplified literature models, this approach allows to quantify a number of additional factors which are critical for successful implementation of cost-effective parts feeding systems, allowing comparison of alternative policies on a consistent basis.

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.

The aim of this paper is to develop a detailed descriptive model for kitting operations, allowing resources sizing and computation of systems’ economic performances.

A mathematical model allows to size resources, given product characteristics and production mix, and determines total system costs by assessing relevant cost items including investment costs (vehicles, containers, storage racks), direct operating costs (transport and kitting workforce, vehicles energy consumption and maintenance, quality costs), indirect operating costs (space requirements, work in process (WIP) and safety stock holding costs, administration and control).

The choice of parts delivery supply to assembly lines requires a thorough economic comparison of alternatives. However, existing models are often simplistic and neglect many critical factors which affect the systems’ performances. As a consequence, industries are unsure about which system is best for their environment. This model allows assessment of the cost and suitability of kitting in any specific industrial setting. Results of the model application are case-specific and cannot be generalized, but the major impact of labour and error correction cost has been highlighted.

The model at present focusses on the in-house kitting systems based on travelling kits concept only. Although all quantitative cost drivers are included, some context-related qualitative decision factors are not yet included. The model assumes that the information about product structure and part requirements is known and that a preliminary design of the assembly system (i.e. line balancing) has been carried out.

Production managers are given a quantitative decision tool to properly assess the implementation of kitting policies at an early decision stage. This allows exploring the trade-offs between the alternatives and properly planning the adoption of kitting systems, as well as comparing kitting with alternative material supply methods.

With respect to previous simplified literature models, this new approach allows quantification of a number of additional factors which are critical for successful implementation of cost-effective kitting systems, including kitting errors. An exhaustive cost estimation of kitting systems in multiple, mixed-model assembly lines is thus permitted.

Outlines current research into multiple co‐operative robots and discusses the practicality of a set of experiments developed to study robot applications better and to verify different solution methodologies. Looks at the design criteria for co‐operating robot systems and describes the laboratory set up to study them.

This paper aims to propose an intelligent system that serves as a cost estimator when new part orders are received from customers.

The methodologies applied in this study were case-based reasoning (CBR), analytic hierarchy process, rule-based reasoning and fuzzy set theory for case retrieval. The retrieved cases were revised using parametric and feature-based cost estimation techniques. Cases were represented using an object-oriented (OO) approach to characterize them in n-dimensional Euclidean vector space.

The proposed cost estimator retrieves historical cases that have the most similar cost estimates to the current new orders. Further, it revises the retrieved cost estimates based on attribute differences between new and retrieved cases using parametric and feature-based cost estimation techniques.

The proposed system was illustrated using a numerical example by considering different lathe machine operations in a computer-based laboratory environment; however, its applicability was not validated in industrial situations.

Different intelligent methods were proposed in the past; however, the combination of fuzzy CBR, parametric and feature-oriented methods was not addressed in product cost estimation problems.

The paper's aim is to assess the impact of product related features on the performances of assembly line manufacturing systems, also providing a specific Design for Manufacturing and Assembly rating index to assess the goodness of a product design solution with respect to assembly line performances.

A computer simulation‐based parametric analysis was carried out to assess the impact of four major product‐related parameters. 216 different assembly line balance problem instances were evaluated. Findings allowed to develop a DFMA rating index specific for assembly line manufacturing as well as design guidelines.

Assembly sequence degrees of freedom and the ratio of the average task duration to the maximum duration are the most influencing parameters. While the former should be maximized, only a moderate task duration variability was found beneficial. The influence of other factors resulted less marked and changing on a case‐specific basis.

Complex interactions between product design features and line performances prevent generalization. The performed numerical experimentation, although extensive, remains somewhat limited respect all possible practical situations. The proposed rating index should be utilized while maintaining an overall perspective about the mutual influence of all parameters. Some suggested guidelines imply a trade off with traditional DFMA guidelines.

Product designers are given useful insights, tools and guidelines to develop better producible products. With the proposed ranking index a designer can easily rate his choices when selecting assembly tasks and sequences, as well as rank alternative product designs solutions.

The paper presents an original discussion about the impact of product design choices on assembly line performances. The developed DFMA rating index and guidelines are new.

This article presents a study on assembly automation in small subcontracting enterprises. In this scenario the evaluated production volumes of each product limit the competitiveness of flexible assembly systems. At the same time the uncertainty of the economic life of the product causes high risk factors in the use of assembly transfer lines. The proposed solution is characterized by the employment of an asynchronous line with single‐purpose automatic stations and manual stations.

The purpose of this paper is to develop analytical planning models to compare just-in-time (JIT) delivery and line storage (LS) alternatives for a continuous supply of materials to assembly lines.

A mathematical model is developed to size resources and to determine total system costs.

The choice of assembly lines feeding policy requires a thorough economic comparison of alternatives. However, the existing models are often simplistic, neglecting many critical factors which affect the systems’ performances. As a consequence, industries are unsure about which system is best for their environment. This model allows to compare the cost and suitability of two major continuous-supply alternatives in any specific industrial setting. Results of the model application are case-specific and cannot be generalized.

The model is aimed at single-model assembly lines operating in a deterministic environment. Although relevant quantitative cost drivers are included, some context-related qualitative factors are not yet included. The model assumes that the information about product structure and part requirements is known and that a preliminary design of the assembly system has been carried out.

Production managers are given a quantitative decision tool to properly assess the implementation of continuous material supply policies at an early decision stage, and determine which option is the best, also allowing to explore trade-offs between the alternatives.

With respect to previous simplified literature models, this new approach allows to quantify a number of additional factors which are critical for the successful implementation of cost-effective continuous-supply systems, including error costs. No other direct comparison of LS and JIT is available in the literature.