Quality Control Tasks Research Articles

A case study assessment of the operational performance of a multiple fresh produce distribution centre in the UK

PurposeThe aim of this research is to evaluate the current operational status of fresh produce distribution centres in the UK and identify the nature and magnitude of the main logistical problems within them.Design/methodology/approachA critical evaluation of space and time utilization efficiency has been achieved by studying on‐site operations in a multiple produce handling and short‐term storage facility in Kent, UK. The objective of this research was to measure operational performance of distribution centres for agricultural perishables in terms of through‐put and space utilization.FindingsThe inefficient utilization of storage space within cold rooms has been identified and quantified accurately, whilst the quality control task has been recognized as the most time‐consuming task and a critical cause for hindering product flow.Practical implicationsDespite their importance, distribution centres for fresh fruit and vegetables have received little attention in the distribution and performance management literature. Given the lack of robust performance measurement systems reported, the measurement of operational performance in distribution centres for agricultural products was a challenge.Originality/valueThe measurement and improvement of the operational performance in each linkage of the fresh produce supply chain – such as a distribution centre – can lead in achieving higher levels of service at substantially reduced costs. A small number of publications are found in the literature providing information on physical distribution of agricultural perishables, and how the key features of perishability and voluminosity of the produce affect the distribution efficiency. In this research, a step towards the improvement of the fresh produce distribution industry operational performance has been attempted, by evaluating the current operational status of a leading multiple produce distribution centre in the UK.

State of the art of ice bearing capacity and ice construction

Abstract Ice is an effective and economical means of supporting loads for construction and resource extraction. The main requirement is to have continuous ice of sufficient thickness to support the intended loadings. Ice has been used to support heavy loads, both mobile and stationary and long-term loads such as oil and gas drilling rigs. It has been used to support the installation of offshore pipelines and related facilities. The paper describes the various uses of ice as a load-bearing medium and presents methods for determining required thicknesses. The bending of floating ice under applied load causes flexural stress to be imposed on the ice cross section. Because ice is weak in tension, the critical stress is the maximum tensile stress at the bottom of the ice directly under the load. The paper presents standard methods of calculating the maximum, extreme fibre stress for different types of loads and presents an allowable stress for safe use of the ice as a load-bearing medium. This allowable stress is also instrumental in ensuring that long term, creep deformation does not result in submergence of the ice surface. The paper presents a method of estimating long-term deflection and also presents a method of assessing the effects of dynamic or moving loads. Grounded ice roads require sufficient thickness to spread applied wheel loads and avoid overstressing of the tundra or seabed. A method of assessing the support provided by widely differing subgrade conditions is presented. Construction methods and techniques for ice roads and structures, including the best types of equipment to use, are presented, with photographs. Issues such as snow removal vs. flooding of thick snow are discussed. Durability of the road surface and surface repairs is outlined. During the construction phase of ice structures, the quality control (QC) tasks verify material quantity and material quality as required by the design. An outline of considerations for this task is presented. Failures and anecdotal information related to the design, construction and use of ice roads and structures are presented, with illustrative photographs.

Optimization of a slurry dispersion method for minerals and trace elements analysis in infant formulae by ICP OES and FAAS

Infant formula developed by manufacturers requires a rigorous control of composition, particularly those elements added routinely in an attempt to mimic the mineral composition of human milk. A total of 97 different types of powdered infant formulae (preterm, adapted starter, adapted follow-up, toddler, specialised and soy-based formulae) commercially available in Spain were studied. It is noteworthy great differences in mineral (Ca, P, Mg) and trace element (Zn, Fe, Cu, Mn) contents found between analysed and listed in label information. The development of a fast, simple and direct slurry method for the determination of these essential micronutrients in infant formula by inductively coupled plasma optical emission spectrometry (ICP OES) and flame atomic absorption spectrometry (FAAS) was performed in order to help in quality control tasks. Infant formula samples were solubilised using different amounts of several different solvents. An addition of 250 μL of a solution 10% tetramethylammonium hydroxide and 25% ammonium hydroxide were required for the accurate quantification of Ca and P, Mg, Zn, Fe, Cu and Mn, respectively. The standard reference material 1549 non-fat milk powder was solubilised to compare the validity of assayed methodology following slurry nebulisation and traditional microwave-assisted acid digestion method. Good agreement of the analytical results by both ICP OES and FAAS, with the certified values was obtained. Method performance parameters (accuracy, precision and methodological detection limits) were determined for studied elements to check the quality and usefulness of the optimised slurry method. The analytical procedure was applied successfully to the analysis of a representative group of infant formulae. Levels of analysed elements were graphically represented, showing an acceptable comparability between slurry and acid-mineralisation method set by linear correlation coefficients and slopes close to the unit. The described simple and slurry method is appropriate, as an attractive alternative, for routine control analysis of added essential elements in infant formulae regardless of predominant protein type used in manufacture.

Efficient Tool for the Scheduling of Multiproduct Pipelines and Terminal Operations

This paper addresses the problem of scheduling a transmission pipeline carrying several petroleum products from a single oil refinery to a unique distribution center over a monthly horizon. The proposed approach is based on a very efficient mixed-integer linear programming (MILP) continuous-time formulation that is capable of determining the optimal pipeline batch sequence and lot sizes as well as the schedule of lot injections in the line and the timing of product deliveries to the distribution terminal. Moreover, the MILP model rigorously accounts for customer product demands on a daily basis, key terminal operations like lot settling periods for quality control tasks, and a predefined set of alternative lot sizes to get better control of tank availability. The approach also does not require the division of pipeline segments into a number of single-product packs of known capacities since the volume scale is also handled in a continuous manner. Results found for several examples involving the schedule of a real-world single-source single-destination multiproduct pipeline under different operational scenarios show that the proposed method leads to better pipeline schedules than previous approaches in a more rigorous way and at much lower computational cost.

Manufacturing e-quality through integrated web-enabled computer vision and robotics

This paper investigates the development of a Web-based quality control system with the use of Internet-based computer machine vision. Such a system allows designers located far from the production facility to monitor, control, and program the quality inspection process as the product design evolves. Quality control tasks are performed and monitored remotely through the Web where Internet-based machine vision sensors inspect part dimensions and tolerance while Internet-enabled robots perform the necessary robotic operations. The remote quality monitoring system—which lets the user monitor the part status including data, image, and video through the Internet—is built using Java. The use of Java allows for interconnection and data transfer between the different components of the Web-based quality system and the robots. The ability to access and control quality control devices via the Web benefits the current manufacturing environment in the following ways: ubiquitous access to the production floor, remote control/programming/monitoring capability, and integration of production equipment into information networks for improving efficiency and product quality.

Practical use of receiver operating characteristic analysis to assess the performances of defect detection algorithms

Defect detection in images is a current task in quality control and is often integrated in partially or fully automated sys- tems. Assessing the performances of defect detection algorithms is thus of great interest. However, because this is application- and context-dependent, it remains a difficult task. We describe a meth- odology to measure the performances of such algorithms on large images in a semi-automated defect inspection situation. Consider- ing standard problems occurring in real cases, we compare typical performance evaluation methods. This analysis leads to the con- struction of a simple and practical receiver operating characteristic (ROC) based method. This method extends the pixel-level ROC analysis to an object-based approach by dilating the ground truth and the set of detected pixels before calculating the true-positive and false-positive rates. These dilations are computed thanks to the a priori knowledge of a human-defined ground truth and gives to true-positive and false-positive rates more consistent values in the semi-automated inspection context. Moreover, the dilation process is designed to be automatically suited to the object's shape in order to be applied on all types of defects without any parameter to be

Utilizing Diverse Feature Data for Reconstruction of Scanned Object as a Basis for Inspection

Inspection of machined objects is one of the most important quality control tasks in the manufacturing industry. Ideally, inspection processes should be able to work directly on scan point data. Scan data, however, are typically very large scale (i.e., many points), unorganized, noisy, and incomplete. Therefore, direct processing of scanned points is problematic. Many of these problems may be reduced if reconstruction methods exploit diverse scan data, that is, information about the properties of the scanned object. This paper describes this concept and proposes new methods for extraction and processing of diverse scan data: (1) extraction (detection of a scanned object’s sharp features by the sharp feature detection method) and (2) processing (scan data reduction by the geometric bilateral filter method). The proposed methods are applied directly on the scanned points and are completely automatic, fast, and straightforward to implement. Finally, this paper demonstrates the integration of the proposed methods into the computational inspection process.

Automated processing of construction specifications to support inspection and quality control

Construction specifications play an important role in communicating quality requirements on a construction project. However, working with these specifications can be cumbersome and error prone due to the large amount of specifications that need to be considered and the dependencies between those specifications. This paper discusses an approach for automating the processing of construction specifications to support inspection and quality control tasks in construction projects. The reasoning approach leverages information available in different types of product and process models to identify specifications applicable to products existing in a project and to extract the requirements imposed by the specifications applicable to each product. The automated identification of applicable specifications and the automated extraction of requirements imposed by these specifications can support and enable automation of tasks, such as inspection and defect detection, which depend on information from construction specifications. Thus, the herein presented specification reasoning approach can be seen as a stepping stone towards automated defect detection on construction sites.

The factory system in the British industrial revolution: A complementarity thesis

This paper offers an explanation for the rise of the factory system in Britain during the Industrial Revolution (1770–1850) based on the concept of complementarity: Investment in machinery, process supervision, and improved quality control formed a cluster of complementary activities in which adopting any one increased the marginal return to also adopting the others. Further, factory owners introduced process supervision not only to increase work effort, but also to balance worker incentives among production, quality control, and asset maintenance tasks. To test this hypothesis, I have constructed a new data set from firm studies and archival records. Measures of firms’ adoption of the activities are positively correlated in the cross-section of firms, providing evidence in favor of the complementarity hypothesis.

Non-destructive evaluation of concrete samples using PGNAA technique

Non-destructive evaluation of concrete is an important task of quality control in building construction industry. The quality evaluation of concrete samples was carried out using prompt gamma ray activation analysis (PGNAA) technique. In this study calcium and silicon contents of six concrete samples were determined through yield of 1.94 MeV gamma-rays from calcium and 3.54 MeV gamma-rays from silicon. The concrete samples were prepared by mixing cement, coarse and fine aggregates in different proportions. A linear correlation has been observed between the experimental yield of the prompt gamma rays and the actual calcium and silicon concentration in the concrete samples. Results of this study have demonstrated successful use of an accelerator-based PGNAA setup in non-destructive analysis of the concrete samples.

Pipeline Scheduling and Inventory Management of a Multiproduct Distribution Oil System

Within the oil supply chain, although refinery operations are extensively studied, distribution center operations are not being explored to their full potential. In this paper, these types of operations are studied. A mixed-integer linear programming (MILP) approach is used to model the problem of oil derivatives pipeline transportation scheduling and supply management. The objective of the model is to attain a high level of operation, satisfying clients and accounting for distribution center restrictions and compulsory tasks. First, a base model is developed, which accounts for product transportation, inventory management, and daily client satisfaction. Later, an extension is presented to account for a settling period for each new lot that arrives at the distribution center. A pumping schedule, including the product sequence, lot volume, and timing issues, is obtained. Also, the inventory management is performed while accounting for daily clients requests and quality control tasks. A continuous represent...

Correlation of cytotechnologists' parameters with their performance in rapid prescreening of papanicolaou smears

Efficient quality control is essential to ensure high sensitivity of Papanicolaou (Pap) smears. For this purpose, rescreening of 10% random negative smears is increasingly felt to be ineffective. Rapid rescreening (RR) of all negative Pap smears is more practical and has received widespread acceptance, especially in Europe, although its sensitivity is difficult to monitor and its retrospective nature may influence the vigilance of the screeners. The method of rapid prescreening (RPS) overcomes these drawbacks because rapid review of Pap smears precedes full screening. All routine conventional Pap smears (n = 8364) over 2 months underwent RPS by 12 cytotechnologists, followed by full screening. Data were analyzed to determine correlation between the RPS sensitivity of individual cytotechnologists and both their sensitivity in full screening and their years of experience as cytotechnologists. There was a striking variability in sensitivity (15.4%-72.7%) among the 12 screeners with an atypical squamous cells of undetermined significance (ASCUS) threshold. There was no correlation between RPS sensitivity of individual cytotechnologists with either their sensitivity in full screening or their years of experience as cytotechnologists. The skills required of a cytotechnologist for achieving a high sensitivity in RPS are apparently different from those of full screening and are independent of the sensitivity of the screeners at full screening or of the years of experience as cytotechnologists.

A Review of Cancer Screening Evaluation Techniques, with some Particular Examples in Breast Cancer Screening

SummaryThe instigation of mass screening for breast cancer has, over the last three decades, raised various statistical issues and led to the development of new statistical approaches. Initially, the design of screening trials was the main focus of research but, as the evidence in favour of population-based screening programmes mounts, a variety of other applications have also been identified. These include administrative and quality control tasks, for monitoring routine screening services, as well as epidemiological modelling of incidence and mortality. We review the commonly used methods of cancer screening evaluation, highlight some current issues in breast screening and, using examples from randomized trials and established screening programmes, illustrate the role that statistical science has played in the development of clinical research in this field.

Trait and state predictors of error detection accuracy in a simulated quality control task

This study examined whether personality traits or mood and workload states are more predictive of detection accuracy in a simulated quality control task mimicking prescription checking in a pharmacy. Ninety-one undergraduate volunteers checked 80 simulated scripts for accuracy in a basic task environment with error rates ranging from 26% to 38%. Four dimensions of perceived workload and three task-related mood factors were assessed multiple times during the task, and several theoretically relevant personality traits were measured before the simulation. Performance was measured using hit rate and false alarm ratios. Results suggested that trait factors were more predictive of hit ratios in this study than were measures of task-related mood and perceived workload. Implications and future research directions are discussed.

Self-regulation, engagement, motivation, and performance in a simulated quality control task.

This study examined how self-regulation and task-related motivation were related to the accuracy of error detection and task engagement in a simulated quality control task that mimicked prescription-checking behavior in a pharmacy. Ninety-one participants completed measures of self-regulation, task engagement, and task-related motivation and then checked 80 simulated scripts with inserted error ratios ranging from 26% to 38%. Motivation and task engagement were assessed at the beginning of the task, the midpoint of the task, and after the task was over. Performance was measured in terms of sensitivity (error detections) and specificity (false alarm responses). Results indicated that motivation was correlated with higher sensitivity, while self-regulation was correlated with lower specificity. Higher mid-task motivation and higher self-regulation were also predictive of greater task engagement at the midpoint of the task only. Results are discussed and future research directions are proposed.

Determination of amount of substance for nanometre‐thin deposits: consistency between XPS, RBS and XRF quantification

AbstractQuantification on the nanometre scale is a key task in quality control and for the development of new materials in nanotechnology. In this paper we have studied the consistency in the determination of the amount of substance found by XPS peak shape analysis, Rutherford backscattering spectroscopy (RBS) and x‐ray fluorescence spectrometry (XRF). To this end, ZnO was deposited by plasma‐enhanced chemical vapour deposition on the three substrates. Four different sets of samples were produced, with the amount of ZnO deposited in the range 1–10 nm. From XPS analysis it is found that ZnO grows in the form of islands on all three substrates. For each system, the analysis was done independently with two XPS peaks from the overlayer with widely different kinetic energy and one XPS peak from the substrate. The growth mechanism found from analysis of each of the three peaks was consistent and the total amount of determined ZnO material was identical to within 15%. The root‐mean‐square deviation from the XPS quantification of the relative AOS was 20% for XRF and 16% for RBS. Because the absolute amount of substance determined from analysis of the three XPS peaks for each sample was consistent, it is concluded that the energy dependence of the applied inelastic mean free paths (taken here from the empirical TPP‐2M formula) is correct. It was found that the absolute amounts of substance determined by RBS and XRF are consistently factors of 2.1 and 1.5 lower than the that determined by XPS peak shape analysis. It is suggested that the main reason for this large discrepancy is inaccuracy in the applied ‘effective’ inelastic electron mean free path. Copyright © 2003 John Wiley & Sons, Ltd.

Signal probability effects on error detection performance in a quality control task.

This study was designed to examine the influence of signal probability on detection accuracy in a quality control task patterned after the checking of prescriptions in a pharmacy. Signal probability was defined as the ratio of erroneous scripts to correct scripts. 91 participants were either exposed to signal probabilities ranging from 26 to 30% ("low probability") or 34 to 38% ("high probability") while checking two sets of 40 simulated scripts for accuracy. Wrong item, wrong number, and wrong label information errors were possible, and performance was measured in terms of sensitivity (percentage of errors detected) and specificity (percentage of correct orders accepted). Analysis indicated that sensitivity was significantly worse for participants in the high signal probability condition, but specificity was not significantly different between signal probability conditions. Connections to existing theory and future directions for research are discussed.

Automatic colour printing inspection by image processing

The inspection of colour printing products constitutes a very important quality control (QC) task in the printing industry. Many defects on such products may be inspected by current commercially available vision systems. However, for the inspection of complex colour prints, the capabilities and performance of available systems are limited. The current practice in the printing industry is to inspect complex colour products manually. This process is labour-intensive and the results are not reliable as they vary with the time, mood and personal skills of the inspectors. In this paper, the authors propose an algorithm to automate the colour prints inspection process, which incorporates colour histogram-based techniques for colour image processing and a neural network for image classification. Preliminary results have shown that this algorithm is able to inspect the defects of complex colour prints under varying illumination conditions.

New developments in fast 3D-surface quality control

Inspection is the process of determining if a product deviates from a given set of specifications. Fast inspection usually involves measurement of specific part features such as assembly integrity, geometric dimensions and surface finish. It is a quality control task, but is distinguished from testing tasks. The visual inspection of 3D parts (car body parts) is a special task within manufacturing that has been automated at a comparatively slow pace up to this time. Different optical methods, applied for 3D measuring at microscopic and macroscopic levels of sheet metal parts, based on the projected fringes method (PFM), electronic speckle interferometry (ESPI), the structured-lighting reflection technique (SLRT), white-light interferometry (WLI) and also SEM-, AFM- and laser scanning methods (LSM) will be discussed. In addition, stylus instruments and also colorimeter measurements are included. The presentation closes with the advantages and disadvantages of different contemporary intelligent methods for car body inspections: neural net based classification, fractal analysis and wavelet transformation.

Optical high-precision three-dimensional vision-based quality control of manufactured parts by use of synthetic images and knowledge for image-data evaluation and interpretation.

Vision-based evaluation of industrial workpieces can make efficient use of knowledge-based approaches, in particular for quality control, inspection, and accurate-measurement tasks. A possible approach is to compare real images with conceptual (synthetic) images generated by use of standard computer-aided design models, which include tolerances and take the application-specific conditions into account (e.g., the measured-calibration data). Integrated in (industrial) real-life environments, our evaluation methods have been successfully applied to on-line inspection of manufactured parts including sculptured surfaces, using structured light techniques for the reconstruction of three-dimensional shapes. Accuracies in the range 15-50 microm are routinely achieved by use of either isolated images or spatially registered image sequences.