Dissimilarity Maximization Method for Real-time Routing of Parts in Random Flexible Manufacturing Systems

This paper presents a dissimilarity maximization method (DMM) for real-time routing selection and compares it via simulation with typical priority rules commonly used in scheduling and control of flexible manufacturing systems (FMSs). DMM aims to reduce the congestion in the system by selecting a routing for each part among its alternative routings such that the overall dissimilarity among the selected routings is maximized. In order to evaluate the performance of DMM, a random FMS, where the product mix is not known prior to production and off-line scheduling is not possible, is selected for the simulation study. A software environment that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to implement the DMM concept. In addition to DMM, the simulation study uses two priority rules for routing (i.e., machine) selection and seven priority rules for selecting parts awaiting service at machine buffers. The results show (1) DMM outperforms the other two routing selection rules on production rate regardless of the part selection rule used, and (2) its performance is highly dependent on the part selection rules it is combined with.     

Conformal radiotherapy of maxilla tumors

PURPOSE: To demonstrate a conventional and a new therapeutic method of 3D treatment planning in maxilla tumors, the process of 3D treatment planning and its significance and to compare these two methods. METHOD: We performed 2D and 3D treatment plans. The ADAC planning system was used in the 3D treatment planning. CT and MRI scans were taken on the target volume and on each scan we demarcated the target volume and the critical organs. The irregular fields were obtained by 3D graphic reconstruction provided by the treatment planning programme. RESULTS: Compared to the conventional treatment planning more favourable dose distribution was obtained within the target volume and the radiation burden of the critical organs was kept under their tolerance doses. CONCLUSION: In conformal 3D treatment planning the shape and size of the irradiated volume are in good conformity with those of the target volume. In this way the radiation burden of the critical organs and adjacent intact tissues can be reduced.     

Red blood cell phenotyping from 3D confocal images using artificial neural networks

The investigation of cell shapes mostly relies on the manual classification of 2D images, causing a subjective and time consuming evaluation based on a portion of the cell surface. We present a dual-stage neural network architecture for analyzing fine shape details from confocal microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a congenital blood disease, namely hereditary spherocytosis. Characteristic shape features are revealed from the spherical harmonics spectrum of each cell and are automatically processed to create a reproducible and unbiased shape recognition and classification. The results show the relation between the particular genetic mutation causing the disease and the shape profile. With the obtained 3D phenotypes, we suggest our method for diagnostics and theragnostics of blood diseases. Besides the application employed in this study, our algorithms can be easily adapted for the 3D shape phenotyping of other cell types and extend their use to other applications, such as industrial automated 3D quality control.     

Exergy based renewability assessment: Case study to ecological wastewater treatment

The renewability assessment has seldom been a core issue in previous studies. This work presents a framework to assess the renewability of a production system based on the unified ecological evaluation method of embodied cosmic exergy analysis. For the first time, both historical renewable and nonrenewable resources uses of each social product input of a system are individually and completely traced and measured by the embodied cosmic exergy as available energy. A set of indicators have also been devised to assess the resources utilization efficiency and renewability of a production system. To demonstrate the framework, a case study is carried out for a pilot constructed wetland wastewater treatment system in Beijing. The resources utilization style and renewability of the case system are analyzed and assessed. The presented framework can be easily transplanted to assess the renewability of other products, which could contribute a lot to meet the goal of sustainable development.     

The possible role of information technology in radiotherapy II. The development of a biological dose distribution model in the 3-dimensional treatment planning of brain tumours

OBJECTIVE: Developing a new medical software based on the utilisation of information technology required in 3-dimensional treatment planning and modern radiotherapy. METHODS: The physical dose distribution programs were converted into biological meaning with the insertion of biological equivalence equations based on LQ model. Biological dose distributions and biological dose-volume histograms were generated. The treatment plans of a brain tumour patient were investigated to determine the dose burdening of the normal central nervous system tissues. RESULTS: Employing 3D conformal method, the dose of the vital mid-line structures decreased significantly, which possesses a more meaningful biological importance. Different treatment plans and different fractionation regimens could be compared to each other by utilising this kind of biological model. CONCLUSION: By employing information technology we succeeded in establishing a theoretical biological dose distribution system that could be visualised. The advantages of 3D treatment planning proved unambiguous. In the future this method will probably be suitable to choose the best therapeutic regimens.     

Comparison of marine spatial planning methods in Madagascar demonstrates value of alternative approaches

The Government of Madagascar plans to increase marine protected area coverage by over one million hectares. To assist this process, we compare four methods for marine spatial planning of Madagascar's west coast. Input data for each method was drawn from the same variables: fishing pressure, exposure to climate change, and biodiversity (habitats, species distributions, biological richness, and biodiversity value). The first method compares visual color classifications of primary variables, the second uses binary combinations of these variables to produce a categorical classification of management actions, the third is a target-based optimization using Marxan, and the fourth is conservation ranking with Zonation. We present results from each method, and compare the latter three approaches for spatial coverage, biodiversity representation, fishing cost and persistence probability. All results included large areas in the north, central, and southern parts of western Madagascar. Achieving 30% representation targets with Marxan required twice the fish catch loss than the categorical method. The categorical classification and Zonation do not consider targets for conservation features. However, when we reduced Marxan targets to 16.3%, matching the representation level of the "strict protection" class of the categorical result, the methods show similar catch losses. The management category portfolio has complete coverage, and presents several management recommendations including strict protection. Zonation produces rapid conservation rankings across large, diverse datasets. Marxan is useful for identifying strict protected areas that meet representation targets, and minimize exposure probabilities for conservation features at low economic cost. We show that methods based on Zonation and a simple combination of variables can produce results comparable to Marxan for species representation and catch losses, demonstrating the value of comparing alternative approaches during initial stages of the planning process. Choosing an appropriate approach ultimately depends on scientific and political factors including representation targets, likelihood of adoption, and persistence goals.     

Multiple-Objective Scheduling for the Hierarchical Control of Flexible Manufacturing Systems

This paper presents a hierarchical approach to scheduling flexible manufacturing systems (FMSs) that pursues multiple performance objectives and considers the process flexibility of incorporating alternative process plans and resources for the required operations. The scheduling problem is solved at two levels: the shop level and the manufacturing system level. The shop level controller employs a combined priority index developed in this research to rank shop production orders in meeting multiple scheduling objectives. To overcome dimensional complexity and keep a low level of work-in-process inventory, the shop controller first selects up to three production orders with the highest ranking as candidates and generates all possible release sequences for them, with or without multitasking. These sequences are conveyed to the manufacturing system controller, who then performs detailed scheduling of the machines in the FMS using a fixed priority heuristic for routing parts of multiple types while considering alternative process plans and resources for the operations. The FMS controller provides feedback to the shop controller with a set of suggested detailed schedules and projected order completion times. On receiving these results, the shop controller further evaluates each candidate schedule using a multiple-objective function and selects the best schedule for execution. This allows multiple performance objectives of an FMS to be achieved by the integrated hierarchical scheduling approach.     

Model-based inverse estimation for active contraction stresses of tongue muscles using 3D surface shape in speech production

This paper presents a novel inverse estimation approach for the active contraction stresses of tongue muscles during speech. The proposed method is based on variational data assimilation using a mechanical tongue model and 3D tongue surface shapes for speech production. The mechanical tongue model considers nonlinear hyperelasticity, finite deformation, actual geometry from computed tomography (CT) images, and anisotropic active contraction by muscle fibers, the orientations of which are ideally determined using anatomical drawings. The tongue deformation is obtained by solving a stationary force-equilibrium equation using a finite element method. An inverse problem is established to find the combination of muscle contraction stresses that minimizes the Euclidean distance of the tongue surfaces between the mechanical analysis and CT results of speech production, where a signed-distance function represents the tongue surface. Our approach is validated through an ideal numerical example and extended to the real-world case of two Japanese vowels, /ʉ/ and /ɯ/. The results capture the target shape completely and provide an excellent estimation of the active contraction stresses in the ideal case, and exhibit similar tendencies as in previous observations and simulations for the actual vowel cases. The present approach can reveal the relative relationship among the muscle contraction stresses in similar utterances with different tongue shapes, and enables the investigation of the coordination of tongue muscles during speech using only the deformed tongue shape obtained from medical images. This will enhance our understanding of speech motor control.     

A novel 3D shape context method based strain analysis on a rat stomach model

The stomach has the ability to change its geometry and volume during digestion. Thus, the stomach shape changes dynamically due to changes in contents and due to pressure from adjacent organs. Full-field strain analysis is therefore important for accurate estimation of the true deformation in this highly non-homogeneous, anisotropic organ. The aim of this study is to introduce a modified non-rigid image registration based 3D shape context method combined with a full-field strain analysis method to describe a distension-induced 3D gastric deformation. The geometry of a normal rat stomach at distension pressures from 0.05 kPa to 0.8 kPa were obtained by ultrasonic scanning. The full-field strain distribution of the 3D gastric model between the reference state and the distended state were computed on the basis of the improved 3D shape context method and full-field strain analysis method. The registered surface showed a good agreement with the real deformed surface for all distension states. However, the errors increased with the distension pressure due to increasing dissimilarity between the deformed and the reference surface. The strain distributions on the stomach surface were non-uniform with the largest deformation in the non-glandular part and the greater and lesser curvature when the pressure was higher than 0.2 kPa. The wall stiffness of the non-glandular part was softer than that of the glandular part. The modelling analysis method which is closely allied with the non-rigid image registration and strain analysis provides a kinematically possible deformation mode of the gastric wall. This method can be potentially used for clinical data estimating the kinematical properties of the human visceral organs in health and disease.     

An NIR-based PAT approach for real-time control of loading in Protein A chromatography in continuous manufacturing of monoclonal antibodies

Control of column loading in Protein A chromatography is a crucial part of development of robust and flexible process platforms for continuous production of monoclonal antibody (mAb) products. In this paper, we propose a control system that uses near infrared spectroscopy (NIRS) flow cells to accomplish the above. Two applications have been demonstrated using a periodic counter-current continuous chromatography setup. The first application involves use of single NIR flow cell before the inlet of the loading column to measure the concentration of mAb in the harvested broth. Measurement was in real-time (every 3 s) and within ±0.05 mg/ml, significantly better than making UV-based concentration estimations. The second application involved use of an additional NIR flow cell at the outlet of the loading column to measure column breakthrough in real time. The concentration data was transferred to a Python-based monitoring and control algorithm layered over a Cadence BioSMB system. The program could successfully run a three-column periodic counter current method on the BioSMB whereas controlling loading to ensure optimal resin utilization in each loading cycle phase based on precharacterized dynamic binding capacity models, whereas maintaining periodic elutions. The system was tested with multiple perturbations in harvest concentration, modeled after deviations that could arise downstream of a perfusion cell culture system. The results show that the proposed control is a spectroscopy-based process analytical technology tool that facilitates real time monitoring and control of loading in process chromatography. It is adaptable to any continuous chromatography equipment and is very well suited for implementation in a continuous mAb production train.     

Model of Red Blood Cell Rotation in the Flow toward a Cell Sizing Orifice: Application to Volume Distribution

The rotation of human red blood cells (RBC) as they flow in the shear field established by a Coulter type orifice is modeled. This model, based on hydrodynamics of ellipsoid rotation in laminar creeping flow, is used to calculate the probability of the cells entering the orifice with a specific orientation. The electrical resistance change produced by a cell passing through the orifice of an electronic cell volume detector is the product of an orientation-dependent shape factor and the cell volume. This paper presents a method to calculate the shape factor probability distribution which can be used to predict its effect on the cell volume distribution. Experimental results confirm the theoretical prediction that the right skewness of resistance change distributions is in part a result of the nonspherical shape of red cells.     

MELODIE: a whole-farm model to study the dynamics of nutrients in dairy and pig farms with crops

In regions of intensive pig and dairy farming, nutrient losses to the environment at farm level are a source of concern for water and air quality. Dynamic models are useful tools to evaluate the effects of production strategies on nutrient flows and losses to the environment. This paper presents the development of a new whole-farm model upscaling dynamic models developed at the field or animal scale. The model, called MELODIE, is based on an original structure with interacting biotechnical and decisional modules. Indeed, it is supported by an ontology of production systems and the associated programming platform DIESE. The biotechnical module simulates the nutrient flows in the different animal, soil and crops and manure sub-models. The decision module relies on an annual optimization of cropping and spreading allocation plans, and on the flexible execution of activity plans for each simulated year. These plans are examined every day by an operational management sub-model and their application is context dependent. As a result, MELODIE dynamically simulates the flows of carbon, nitrogen, phosphorus, copper, zinc and water within the whole farm over the short and long-term considering both the farming system and its adaptation to climatic conditions. Therefore, it is possible to study both the spatial and temporal heterogeneity of the environmental risks, and to test changes of practices and innovative scenarios. This is illustrated with one example of simulation plan on dairy farms to interpret the Nitrogen farm-gate budget indicator. It shows that this indicator is able to reflect small differences in Nitrogen losses between different systems, but it can only be interpreted using a mobile average, not on a yearly basis. This example illustrates how MELODIE could be used to study the dynamic behaviour of the system and the dynamic of nutrient flows. Finally, MELODIE can also be used for comprehensive multi-criterion assessments, and it also constitutes a generic and evolving framework for virtual experimentation on animal farming systems.     

MDSPACE: Extracting Continuous Conformational Landscapes from Cryo-EM Single Particle Datasets Using 3D-to-2D Flexible Fitting based on Molecular Dynamics Simulation

This article presents an original approach for extracting atomic-resolution landscapes of continuous conformational variability of biomolecular complexes from cryo electron microscopy (cryo-EM) single particle images. This approach is based on a new 3D-to-2D flexible fitting method, which uses molecular dynamics (MD) simulation and is embedded in an iterative conformational-landscape refinement scheme. This new approach is referred to as MDSPACE, which stands for Molecular Dynamics simulation for Single Particle Analysis of Continuous Conformational hEterogeneity. The article describes the MDSPACE approach and shows its performance using synthetic and experimental datasets.     

ShapeRotator: An R tool for standardized rigid rotations of articulated three‐dimensional structures with application for geometric morphometrics

The quantification of complex morphological patterns typically involves comprehensive shape and size analyses, usually obtained by gathering morphological data from all the structures that capture the phenotypic diversity of an organism or object. Articulated structures are a critical component of overall phenotypic diversity, but data gathered from these structures are difficult to incorporate into modern analyses because of the complexities associated with jointly quantifying 3D shape in multiple structures. While there are existing methods for analyzing shape variation in articulated structures in two‐dimensional (2D) space, these methods do not work in 3D, a rapidly growing area of capability and research. Here, we describe a simple geometric rigid rotation approach that removes the effect of random translation and rotation, enabling the morphological analysis of 3D articulated structures. Our method is based on Cartesian coordinates in 3D space, so it can be applied to any morphometric problem that also uses 3D coordinates (e.g., spherical harmonics). We demonstrate the method by applying it to a landmark‐based dataset for analyzing shape variation using geometric morphometrics. We have developed an R tool (ShapeRotator) so that the method can be easily implemented in the commonly used R package geomorph and MorphoJ software. This method will be a valuable tool for 3D morphological analyses in articulated structures by allowing an exhaustive examination of shape and size diversity.     

Predicting the shapes of bones at a joint: application to the shoulder

This paper presents a novel method to explore the intrinsic morphological correlation between the bones of a shoulder joint (humerus and scapula). To model this correlation, canonical correlation analysis (CCA) is used. We also propose a technique to predict a three-dimensional (3D) bone shape from its adjoining segment at a joint based on partial least squares regression (PLS). The high dimensional 3D surface information of a bone is represented by a few variables using principal component analysis, which also captures the pattern of variability of the shapes in our datasets. Our results show that the humerus set and scapula set have highly linear morphological relationship and that the correlation information can be used as a classifier. In this study, primate shoulder bone datasets were categorised into two clusters: great apes (including humans) and monkeys. A leave one out experiment was performed to test the robustness of this prediction method. The prediction behaviour using this method shows statistically significantly better results than using the mean shape from the training set.     

A Genetic-Based Vision System for Cross-Functional Integration in Flexible Manufacturing: A Tutorial and Application

Machine vision has the potential to significantly impact both quality and productivity in automated manufacturing, due to its versatility, flexibility, and relative speed. Unfortunately, algorithmic development has not kept pace with advances in vision hardware technology, particularly in the areas of analysis and decision making. In this article, a tutorial is presented that explains how a genetic algorithm can be applied to vision systems for shape analysis and quality assessment. The control parameters for the algorithm are optimized by conducting experiments of Taguchi's approach to parameter design. The main objective behind this algorithm is to explain an application of the vision system that uses upstream design data of machined parts of different types for downstream metrology and quality decision making in the environment of flexible manufacturing. The part types used for demonstration are restricted to planar polygonal profiles generated by projecting 3D objects onto a 2D inspection plane. The input to the system is a set of boundary features of the part being analyzed, and the outputs from the system include the estimators of size, orientation, position, and out-of-profile error of the part. The system can analyze machined parts of different types without modifying software programs and parameter settings, which makes it generic and flexible, and is inherently suitable for on-line implementation in FMS environments.     

Environmental sustainability of orthopedic devices produced with powder bed fusion

Additive manufacturing consists in melting metallic powders to produce objects from 3D data, layer upon layer. Its industrial applications range from automotive, biomedical (e.g., prosthetic implants for dentistry and orthopedics), aeronautics and others. This study uses life cycle assessment to evaluate the possible improvement in environmental performance of laser‐based powder bed fusion additive manufacturing systems on prosthetic device production. Environmental impacts due to manufacturing, use, and end of life of the designed solution were assessed. In addition, two powder production technologies, gas atomization (GA) and plasma atomization (PA), were compared in order to establish the most sustainable one. Production via traditional subtractive technologies and the additive manufacturing production were also compared. 3D building was found to have a significant environmental advantage compared to the traditional technology. The powder production process considerably influences on a damage point of view the additive manufacturing process; however, its impact can be mitigated if GA powders are employed.