Unwanted Deviations Research Articles

Monatomic phase change memory.

Phase change memory has been developed into a mature technology capable of storing information in a fast and non-volatile way1-3, with potential for neuromorphic computing applications4-6. However, its future impact in electronics depends crucially on how the materials at the core of this technology adapt to the requirements arising from continued scaling towards higher device densities. A common strategy to fine-tune the properties of phase change memory materials, reaching reasonable thermal stability in optical data storage, relies on mixing precise amounts of different dopants, resulting often in quaternary or even more complicated compounds6-8. Here we show how the simplest material imaginable, a single element (in this case, antimony), can become a valid alternative when confined in extremely small volumes. This compositional simplification eliminates problems related to unwanted deviations from the optimized stoichiometry in the switching volume, which become increasingly pressing when devices are aggressively miniaturized9,10. Removing compositional optimization issues may allow one to capitalize on nanosize effects in information storage.

Technique of Monitoring a Human Operator’s Behavior in Man-Machine Systems

Monitoring a human operator’s behavior in man-machine systems is aimed at detecting and diagnosing unwanted behavioral deviations of a human operator from the preset sequence of actions, taking into account their possible response to the current state of the system. The human operator’s behavior is described using the nondeterministic finite-state machine (FSM) model. Techniques for constructing and determinizating this model are proposed to ensure the minimal possible loss of information. The solution of the task is illustrated by the example of working IT system operators.

Radiation therapists’ compliance to a palliative imaging protocol: a case report

AbstractBackgroundImaging protocols are implemented to identify and minimise set-up errors. A crucial component to the success of these protocols is staff compliance.Materials and methodsThis is case report describing a retrospective review of radiation therapists’ compliance to a palliative imaging protocol in a single large institution in one calendar year.ResultsThe review showed a non-compliance to protocol for 8% of treatments. The most frequent protocol deviation was a failure to calculate the mean set-up displacement after 2/3 days of consecutive imaging.ConclusionDespite the presence of institutional evidence-based palliative imaging protocol unwanted deviations in practice can occur.

Compensation of the spatial deviations of measuring elements in CAD

The object of research is the processes of computer-aided design of the elements of complex measuring instruments intended to work under conditions of significant deviations in space caused by mechanical or thermal stresses. One of the most problematic places is that any protection state completely eliminates unwanted deviations of the elements. This is especially true for measurement objects that have large dimensions (tens of meters) and weight, opacity, high temperatures (hundreds of degrees), significant external influences of unpredictable nature, and the like. Models of behavior of such objects under load are extremely complex, and methods of their analysis and use in CAD are not available at all, which leads to the laying of significant errors of the future measurement already at the design stage. In the course of the study, the theory of analysis of technical systems, the theory of measurements, the theory of the resistance of materials and oscillations, the theory of computer-aided design were used. To develop a capacitive method for measuring the density of parts of large-sized reinforced concrete objects from heterogeneous materials, methods of pattern recognition and a virtual object are used. Theoretical and experimental virtual models of electrical characteristics of the elements of measuring instruments and models of their deviation are obtained. Models are used in automated design systems for complex means of capacitive measurement of concrete. The first is mathematical, in which compensation is performed solely by making changes to the measurement results. The second is mechanical, in which compensation is made by changing the geometry of the measuring tool (with static deviation) or depreciation of their elements (with dynamic). Thanks to this, it is possible to create a new subsystem of CAD «DEVICOM», with the help of which shock absorbers were designed to control the technological process of manufacturing the reinforced concrete product «Power transmission line support», which, as a result, reduced the amount of defective products by 7.4 %.

A variation risk management methodology for an interactive pharmaceutical design and manufacturing environment

The pharmaceutical manufacturing field is one of the most challenging fields due to stringent regulations, global harmonization and tough competition. It has been realized that quality, safety and efficacy of pharmaceutical drug products are key elements for success in market. However, improving quality requires better understanding of the product and process critical quality attributes (CQAs). The utmost goal is to build quality upfront during early design stages by implementing guidelines such as quality by design which focuses on targeting design quality into the ingredients, formulation and manufacturing process to deliver the intended performance of the drug product. Achieving such goal is possible by integrating important tools and functions in one interactive usable model. One significant opportunity has been found in the effective utilization of data gathered during different activities such as sampling and testing of pharmaceutical ingredients and products. Extracting patterns of interest of such data can be essential in targeting problems such as variation initiation and variation propagation. Variations are those unwanted deviations from nominal values which greatly impact the final quality and efficacy of products. Manufacturers face some challenges due to lack of quantitative models to prioritize CQAs and quantify their associated risk of variation. Therefore, there is a need for proactive quantitative mechanisms usable during the early design stages to reduce design’s sensitivity to manufacturing variations. The work here introduces a systematic interactive environment that integrates together the design model and the current process capabilities to capture the impact of manufacturing variations on top performance function. A case study on tablet’s crushing strength, expressed by tablet’s tensile strength, has been carried out successfully to prove the effectiveness of the proposed methodology in identifying design’s CQAs and assessing their risk of variation. Moreover, it introduces the mechanism for a quantitative ongoing monitoring of the risk of variation and decision making regarding manufacturers selection.

An interactive variation risk management environment to assess the risk of manufacturing variations

Recently, many manufacturing industries have adopted the methods of “Key Characteristics” (KCs) to identify and analyze product and process critical attributes which need extra control on several levels: product, assembly, sub-assembly, part and process to trace manufacturing variations. Manufacturing variations are those unwanted deviations from nominal values which significantly impact product’s quality, performance and cost. However, those manufacturers face some challenges in the implementation of such procedures. This is due to lack of quantitative models to prioritize those (KCs) and quantify their associated risk of variation. Therefore, there is a need for proactive quantitative mechanisms which incorporate knowledge about the current process capability by communicating Process Capability Data (PCD) during the early design stages to reduce design’s sensitivity to manufacturing variations. The present work builds a systematic interactive environment between the design model and the current process capabilities to analyze PCD which processed and stored in designated databases along with proactive mechanisms to capture the impact of manufacturing variations on performance. It prioritizes and quantifies expected future variations due to possible deviations of the design parameters from their nominal values to assess the related risk of variation. This study comes under the broadest risk management procedure to establish for a novel variation risk management methodology works in an interactive design and manufacturing environment. A case study of a connector beam for an edge card has been carried out successfully to prove the effectiveness of the present methodology in quantifying manufacturing variations and assessing their associated risk of variation.

A multiobjective interval goal programming method using penalty function

This article demonstrates how the penalty function can efficiently be used for solving multiobjective linear programming problem with interval valued objective functions. In the proposed approach, first the target intervals are obtained for the defined objectives. Then, using interval arithmetic and the concept of interval goal programming (IGP) the interval goals are transformed into crisp goals. In the process of solution, the goal achievement function is constructed as a convex combination of the sum of total penalty and the maximum penalty associated with unwanted deviations of the respective goals. Numerical examples are provided to illustrate the proposed approach.

A multiobjective interval goal programming method using penalty function

This article demonstrates how the penalty function can efficiently be used for solving multiobjective linear programming problem with interval valued objective functions. In the proposed approach, first the target intervals are obtained for the defined objectives. Then, using interval arithmetic and the concept of interval goal programming (IGP) the interval goals are transformed into crisp goals. In the process of solution, the goal achievement function is constructed as a convex combination of the sum of total penalty and the maximum penalty associated with unwanted deviations of the respective goals. Numerical examples are provided to illustrate the proposed approach.

Framework to manage multiple goals in community-based energy sharing network in smart grid

Abstract Smart grid has opened up a new role of “prosumer” in an energy value network, transforming many conventional energy consumers into prosumers, who not only generate green energy but also share the surplus with utilities and other consumers. The concept of a goal-oriented prosumer community group (PCG) has emerged recently as an effective way to fulfill sustainable energy exchange. Such community-based energy sharing networks comprise multiple irreconcilable objectives such as demand constraints, cost constraints, and income maximization. In many cases, one goal may be achievable only at the expense of other goals. This necessitates the development of an effective framework to manage the multiple goals and reduce the gap with their achievement levels. Therefore, in this research paper, an effective framework is developed to negotiate among the multiple goals and thus to define optimal mutual goals for each PCG in a more sustainable manner using multiple-criteria goal programming techniques. Simulation results are presented to illustrate how the methods work in practical situations, where each of the objective measure is given a target value and the unwanted deviations from this set are minimized in an achievement function.

Diet models with linear goal programming: impact of achievement functions

Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very sensitive to the type of achievement function that is chosen.This paper aims to provide a methodological insight into several achievement functions. It describes the extended GP (EGP) achievement function, which enables the decision maker to use either a MinSum achievement function (which minimizes the sum of the unwanted deviations) or a MinMax achievement function (which minimizes the largest unwanted deviation), or a compromise between both. An additional advantage of EGP models is that from one set of data and weights multiple solutions can be obtained. We use small numerical examples to illustrate the 'mechanics' of achievement functions. Then, the EGP achievement function is demonstrated on a diet problem with 144 foods, 19 nutrients and several types of palatability constraints, in which the nutritional constraints are modeled with fuzzy sets. Choice of achievement function affects the results of diet models. MinSum achievement functions can give rise to solutions that are sensitive to weight changes, and that pile all unwanted deviations on a limited number of nutritional constraints. MinMax achievement functions spread the unwanted deviations as evenly as possible, but may create many (small) deviations. EGP comprises both types of achievement functions, as well as compromises between them. It can thus, from one data set, find a range of solutions with various properties.

Standard goal programming with fuzzy hierarchies: a sequential approach

This paper proposes a pragmatic model for multi-objective decision-making processes involving clusters of objectives which have a decisional meaning for the decision maker (DM). We provide the DMs with a comfortable tool that allows them to express their preferences both by comparing criteria of the same cluster and via the comparison between the different clusters. In standard goal programming the importance of the goals is modeled by the introduction of preferential weights or/and the incorporation of pre-emptive priorities. However, in many cases the DM is not able to establish a precise preference structure. Even in the case of precise weights the solution does not match necessarily the relative weights or, in the case of precise pre-emptive priority, the result could be very restrictive. In order to overcome these drawbacks, in this paper the normalized unwanted deviations are interpreted in terms of achievement degrees of the goals and fuzzy relations are used to model the relative importance of the goals. Thus, we show how several methodologies from the fuzzy goal programming literature can be tailored for solving standard GP problems. We apply this new modeling to problems where there is a "natural" clustering between goals of the same class. We address this situation by solving two phases; in the first one each class is handled separately taking into account the hierarchy of their goals and, in the second phase, we integrate the results of the first phase and the imprecise hierarchy of the different classes. We formulate a new goal programming model called as sequential goal programming with fuzzy hierarchy model. Because many real situations involve decision making in this environment, our proposal can be a useful tool of broad application. A numerical example illustrates the methodology.

A group decision making model based on goal programming with fuzzy hierarchy: an application to regional forest planning

In this paper a multi-criteria group decision making model is presented in which there is a heterogeneity among the decision makers due to their different expertise and/or their different level of political control. The relative importance of the decision makers in the group is handled in a soft manner using fuzzy relations. We suppose that each decision maker has his/her preferred solution, obtained by applying any of the techniques of distance-based multi-objective programming [compromise, goal programming (GP), goal programming with fuzzy hierarchy, etc.]. These solutions are used as aspiration levels in a group GP model in which the differences between the unwanted deviations are interpreted in terms of the degree of achievement of the relative importance amongst the group members. In this way, a group GP model with fuzzy hierarchy (Group-GPFH) is constructed. The solution for this model is proposed as a collective decision. To show the applicability of our proposal, a regional forest planning problem is addressed. The objective is to determine tree species composition in order to improve the values achieved by Pan-European indicators for sustainable forest management. This problem involves stakeholders with competing interests and different preference schemes for the aforementioned indicators. The application of our proposal to this problem allows us to be able to comfortably address all these issues. The results obtained are consistent with the preferences of each stakeholder and their hierarchy within the group.

From Profile to Surface Monitoring: SPC for Cylindrical Surfaces Via Gaussian Processes

Quality of machined products is often related to the shapes of surfaces that are constrained by geometric tolerances. In this case, statistical quality monitoring should be used to quickly detect unwanted deviations from the nominal pattern. The majority of the literature has focused on statistical profile monitoring, while there is little research on surface monitoring. This paper faces the challenging task of moving from profile to surface monitoring. To this aim, different parametric approaches and control-charting procedures are presented and compared with reference to a real case study dealing with cylindrical surfaces obtained by lathe turning. In particular, a novel method presented in this paper consists of modeling the manufactured surface via Gaussian processes models and monitoring the deviations of the actual surface from the target pattern estimated in phase I. Regardless of the specific case study in this paper, the proposed approach is general and can be extended to deal with different kinds of surfaces or profiles.

An appearance-based measure of surface defects

Surface defects on sheet metal panels such as local out-of-plane geometric deviations, cause unwanted deviations from the intended visual appearance. In the automobile industry, these defects are commonly graded for visual acceptability through reflection analysis on the hardware. This widely used method is unfortunately subjective and thus has low repeatability. The same method can be applied on simulated sheet metal panels by the use of ray-tracing. In this paper we present an objective, appearance-based, measure by formalising the approach of subjective reflection analysis. Hence, a natural connection between an objective measure and the appearance is obtained making it easy to establish acceptable levels. The performance of this measure and three other objective measures is discussed and demonstrated for a real panel and a panel geometry obtained through sheet forming simulations. These examples illustrate that different measures yield different information about the geometry, and the proposed measure gives a useful quantification of the visual appearance deviation.

Multi-period lot-sizing with supplier selection using achievement scalarizing functions

In this paper, an integration of Analytic Network Process (ANP) and achievement scalarizing functions is proposed to choose the best suppliers and define the optimum quantities among the selected suppliers by considering tangible–intangible criteria and time horizon. To reflect the decision maker’s (DM’s) preferences more accurate, an additive achievement function is defined consist of several components. In this additive function while unwanted deviations from periodic budget and aggregate quality goals are balanced by Minmax Goal Programming (MGP), and unwanted deviations from total cost, total value of purchasing (TVP) and aggregate quality are minimized by Achimedean Goal Programming (AGP) to provide more acceptable solutions. This multi-period model enables us to reflect DM’s preferences more flexible than the other traditional models that use only one type of achievement function. The sensitivity analysis was also performed for different levels of periodic demands. It is also possible to enlarge the sensitivity analyses for other parameters such as different levels of capacity, and different weights of components.

A process approach in measuring quality costs of construction projects: model development

One of the most effective tools for evaluating the success of a quality management programme is the measurement of quality costs (prevention, appraisal and failure costs). The application of the concept of quality costs originated in the manufacturing industry in the early 1950s. As increasing attention has been given to improving the overall quality in the construction process since the early 1980s, the application of total quality management (TQM) practices in the construction industry has gained much popularity. A systematic approach is needed for measuring quality costs, especially in the construction industry, due to the great number and complexity of activities involved in a typical project. This paper describes how a simple methodology can be used to capture quality costs in construction projects. Pre-existing models for capturing construction quality costs, by Davis, by Abdul-Rahman, by Low and Yeo and by others, recognize quality cost components but do not address the causes or sources of unwanted deviations. This paper proposes an alternative approach, based on the process cost model and in conformance with BS6143 (1992), which is thought to better facilitate the fundamental goal of TQM, i.e. continual process improvement. A number of professionals involved in construction quality management were interviewed and responded favourably to the practicality of the proposed framework in the construction context.

Phase quantization of a grating without altering the diffraction pattern

Quantization of the phase-delay profile of a diffractive optical element often leads to unwanted deviations of considerable extent in the diffraction pattern. A method for avoiding this flaw for periodic phase gratings is described. The idea is to forgo strict periodicity and use the new degrees of freedom thus obtained to compensate for quantization-related deviations. The method is demonstrated for Fourier-array illuminator gratings designed with an iterative Fourier-transform algorithm.

Dual-mode disturbance-accommodating pointing controller for Hubble Space Telescope

Cyclic thermal expansions and mechanical stiction effects in the solar arrays on the Hubble Space Telescope (HST) are triggering repeated occurrences of damped, relaxation-type flex-body vibrations of the solar arrays. Those solar array vibrations are, in turn, causing unwanted deviations of the telescope from its specified pointing direction. In this paper we propose two strategies one can adopt in designing a telescope-pointing controller to cope with the aforementioned disturbances: 1) a total isolation (TI) control strategy whereby the HST controller torques are designed to adaptively counteract and cancel out the persistent disturbing torques that are causing the unwanted telescope motions and 2) an array damping (AD) control strategy whereby the HST controller torques are used to actively augment the natural dampening of the solar array vibrations and the attendant telescope motions, between triggerings of the stiction-related flex-body relaxation oscillations. Using the principles of disturbance accommodation control theory, a dual-mode controller for a generic, planar-motion (single-axis) model of the HST is proposed. This controller incorporates both the TI and AD modes of disturbance accommodation. Simulation studies of the closed-loop system using generic parameter values clearly indicate, qualitatively, the enhanced pointing performance such a controller can achieve.

Consideration of parasitic bypass couplings in overmoded cavity filter designs

Parasitic bypass couplings-occurring especially in compact higher order mode cavity filters-cause evident deterioration of the desired ideal responses. The study of a TE/sub 301/ mode cavity filter design gives an explanation of the reasons of such unwanted couplings. Based on this knowledge, corrective measures are established and experimentally verified to compensate for unwanted deviations from the ideal filter response. Moreover, this kind of bypass coupling can be utilized to improve the response in advanced cavity filter designs. >