Design trade-offs in self-management technology: the HeartMan case

ABSTRACT

Health self-management technology has the potential to significantly improve the Quality of Life of patients suffering from chronic diseases. However, designing the technology involves numerous highly context-dependent design decisions. In this paper, we analyse a case study of self-monitoring technology in the field of congestive heart failure. We analyse the design process of the technology from the perspective of design trade-offs. Three important trade-offs related to health self-monitoring technology are described in detail, related to patient autonomy, technology appropriation, and patient well-being. For each of the trade-offs, various mediating factors that influence design decisions are described in detail. On a practical level, this analysis can inform future developments in self-management technology. In addition, this design trade-off analysis provides intermediary knowledge that can contribute to a better theoretical understanding of health self-management technology.     

Workers’ rest allowance and smoothing of the workload in assembly lines

Ergonomic aspects have a crucial role in manual assembly systems. They impact on the workers’ health, final product quality and productivity. For these reasons, there is the necessity to integrate them into the assembly line balancing phase as, whereas, only time and cost variables are considered. In this study, human energy expenditures are considered as ergonomic aspects and we integrate them, for the first time, into the assembly line balancing problem type 2 through the rest allowance evaluation. We consider as an objective function the minimization of the smoothness index. Firstly, a new optimal method based on mixed integer linear programming and a new linearization methodology are proposed. Then, a heuristic approach is introduced. To complete the study, a computational experimentation is presented to validate the mathematical model and to compare the methodologies proposed in terms of computational time, complexity and solution. Additionally, we provide a detailed analysis of the impact that rest allowance evaluation can have on productivity comparing the results obtained, taking into account the rest allowance integration before, during and after the assembly balancing process.     

Relationships between the accumulative damage and dielectric properties of woven BN-coated Hi-Nicalon™ SiC fibre-reinforced SiC matrix composites

The accumulative damage behaviour of BN-coated Hi-Nicalon™ SiC fibre-reinforced SiC matrix composite was examined under tensile cyclic loading at room and elevated temperatures. The accumulative damage occurring during the cyclic loading was quantitatively characterised using the damage parameter obtained by the hysteresis loop curves. The damage parameter increased with increasing applied stress beyond the matrix cracking stress, and it subsequently retained a nearly constant value until just before fracture. Moreover, the dielectric constant, dielectric loss and loss tangent of the composite were measured before and after the fracture in the frequency range 1–1000 MHz. The dielectric properties had similar frequency dependency before and after the fracture. However, the dielectric constant, dielectric loss and loss tangent were lower in the post-fractured specimens than in the pristine ones. The reduction of the dielectric properties was associated with the accumulative damage stored in the specimens. In addition, the relationships between the dielectric properties and the damage parameter were described in detail.     

Simultaneous process optimization and heat integration based on rigorous process simulations

This paper introduces a simultaneous process optimization and heat integration approach, which can be used directly with the rigorous models in process simulators. In this approach, the overall process is optimized utilizing external derivative-free optimizers, which interact directly with the process simulation. The heat integration subproblem is formulated as an LP model and solved simultaneously during optimization of the flowsheet to update the minimum utility and heat exchanger area targets. A piecewise linear approximation for the composite curve is applied to obtain more accurate heat integration results. This paper describes the application of this simultaneous approach for three cases: a recycle process, a separation process and a power plant with carbon capture. Case study results indicate that this simultaneous approach is relatively easy to implement and achieves higher profit and lower operating cost and, in the case of the power plant example, higher net efficiency than the sequential approach.     

A modified particle swarm optimization with multiple subpopulations for multimodal function optimization problems

In this paper, a modified particle swarm optimization (PSO) algorithm is developed for solving multimodal function optimization problems. The difference between the proposed method and the general PSO is to split up the original single population into several subpopulations according to the order of particles. The best particle within each subpopulation is recorded and then applied into the velocity updating formula to replace the original global best particle in the whole population. To update all particles in each subpopulation, the modified velocity formula is utilized. Based on the idea of multiple subpopulations, for the multimodal function optimization the several optima including the global and local solutions may probably be found by these best particles separately. To show the efficiency of the proposed method, two kinds of function optimizations are provided, including a single modal function optimization and a complex multimodal function optimization. Simulation results will demonstrate the convergence behavior of particles by the number of iterations, and the global and local system solutions are solved by these best particles of subpopulations.     

A semicontinuous approach for heterogeneous azeotropic distillation processes

The separation of azeotropes has substantial energy and investment costs, and the available methods require high capital costs for reconstruction of process plants. As an alternative, a semicontinuous configuration that utilizes an existing plant with minor modifications has been explored. In this paper, a semicontinuous, heterogeneous azeotropic distillation process is proposed and acetic acid dehydration process is used as a case study. To carry out the simulation work, Aspen HYSYS^® simulation software is used along with MATLAB^® and an interface program to handle the mode-transition of the semicontinuous process. Sensitivity analyses on operating parameters are performed to identify the process limits. Comparisons are made to conventional heterogeneous azeotropic distillation, and dividing-wall distillation column on the annual cost. The results proved that the semicontinuous system is the best setup in terms of total annual costs and energy requirements.     

Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.     

Parallel chaos optimization algorithm with migration and merging operation

Chaos optimization algorithm (COA) utilizes the chaotic maps to generate the pseudo-random sequences mapped as the decision variables for global optimization applications. A kind of parallel chaos optimization algorithm (PCOA) has been proposed in our former studies to improve COA. The salient feature of PCOA lies in its pseudo-parallel mechanism. However, all individuals in the PCOA search independently without utilizing the fitness and diversity information of the population. In view of the limitation of PCOA, a novel PCOA with migration and merging operation (denoted as MMO-PCOA) is proposed in this paper. Specifically, parallel individuals are randomly selected to be conducted migration and merging operation with the so far parallel solutions. Both migration and merging operation exchange information within population and produce new candidate individuals, which are different from those generated by stochastic chaotic sequences. Consequently, a good balance between exploration and exploitation can be achieved in the MMO-PCOA. The impacts of different one-dimensional maps and parallel numbers on the MMO-PCOA are also discussed. Benchmark functions and parameter identification problems are used to test the performance of the MMO-PCOA. Simulation results, compared with other optimization algorithms, show the superiority of the proposed MMO-PCOA algorithm.     

Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems – Part 2: Constrained optimization

This paper is the second one of the two papers entitled “Weighted Superposition Attraction (WSA) Algorithm”, which is about the performance evaluation of the WSA algorithm in solving the constrained global optimization problems. For this purpose, the well-known mechanical design optimization problems, design of a tension/compression coil spring, design of a pressure vessel, design of a welded beam and design of a speed reducer, are selected as test problems. Since all these problems were formulated as constrained global optimization problems, WSA algorithm requires a constraint handling method for tackling them. For this purpose we have selected 6 formerly developed constraint handling methods for adapting into WSA algorithm and analyze the effect of the used constraint handling method on the performance of the WSA algorithm. In other words, we have the aim of producing concluding remarks over the performance and robustness of the WSA algorithm through a set of computational study in solving the constrained global optimization problems. Computational study indicates the robustness and the effectiveness of the WSA in terms of obtained results, reached level of convergence and the capability of coping with the problems of premature convergence, trapping in a local optima and stagnation.