QoS-aware Metamorphic Testing: An Elevation Case Study

Elevators are among the oldest and most widespread transportation systems, yet their complexity increases rapidly to satisfy customization demands and to meet quality of service requirements. Verification and validation tasks in this context are costly, since they rely on the manual intervention of domain experts at some points of the process. This is mainly due to the difficulty to assess whether the elevators behave as expected in the different test scenarios, the so-called test oracle problem. Metamorphic testing is a thriving testing technique that alleviates the oracle problem by reasoning on the relations among multiple executions of the system under test, the so-called metamorphic relations. In this practical experience paper, we report on the application of metamorphic testing to verify an industrial elevator dispatcher. Together with domain experts from the elevation sector, we defined multiple metamorphic relations that consider domain-specific quality of service measures. Evaluation results with seeded faults show that the approach is effective at detecting faults automatically

Design, Implementation and Evaluation of Reinforcement Learning for an Adaptive Order Dispatching in Job Shop Manufacturing Systems

Modern production systems tend to have smaller batch sizes, a larger product variety and more complex material flow systems. Since a human oftentimes can no longer act in a sufficient manner as a decision maker under these circumstances, the demand for efficient and adaptive control systems is rising. This paper introduces a methodical approach as well as guideline for the design, implementation and evaluation of Reinforcement Learning (RL) algorithms for an adaptive order dispatching. Thereby, it addresses production engineers willing to apply RL. Moreover, a real-world use case shows the successful application of the method and remarkable results supporting real-time decision-making. These findings comprehensively illustrate and extend the knowledge on RL

Genetic and tabu search approaches for optimizing the hall call-car allocation problem in elevator group systems

The most common problem in vertical transportation using elevator group appears when a passenger wants to travel from a floor to other different floor in a building. The passenger makes a hall call by pressing a landing call button installed at the floor and located near the cars of the elevator group. After that, the elevator controller receives the call and identifies which one of the elevators in the group is most suitable to serve the person having issued the call. In this paper, we have developed different elevator group controllers based on genetic and tabu search algorithms. Even though genetic algorithm has been previously considered in vertical transportation problems, the use of tabu search approaches is a novelty in vertical transportation and has not been considered previously. Tests have been carried out for high-rise buildings considering diverse sizes in the group of cars. Results indicate that the waiting time and journey time of passengers were significantly improved when dealing with such soft computing approaches. Also, a quickly evaluable solution quality function in the algorithms allows suitable computational times for industry implementation

Genetic algorithm for controllers in elevator groups: analysis and simulation during lunchpeak traffic

The efficient performance of elevator group system controllers becomes a first order necessity when the buildings have a high utilisation ratio of the elevators, such as in professional buildings. We present a genetic algorithm that is compared with traditional controller algorithms in industry applications. An ARENA simulation scenario is created during heavy lunchpeak traffic conditions. The results allow us to affirm that our genetic algorithm reaches a better performance attending to the system waiting times than THV algorithm

Performance-Driven Metamorphic Testing of Cyber-Physical Systems

Cyber-physical systems (CPSs) are a new generation of systems, which integrate software with physical processes. The increasing complexity of these systems, combined with the un certainty in their interactions with the physical world, makes the definition of effective test oracles especially challenging, facing the well-known test oracle problem. Metamorphic testing has shown great potential to alleviate the test oracle problem by exploiting the relations among the inputs and outputs of different executions of the system, so-called metamorphic relations (MRs). In this article, we propose an MR pattern called PV for the identification of performance-driven MRs, and we show its applicability in two CPSs from different domains, which are automated navigation systems and elevator control systems. For the evaluation, we as sessed the effectiveness of this approach for detecting failures in an open-source simulation-based autonomous navigation system, as well as in an industrial case study from the elevation domain. We derive concrete MRs based on the PV pattern for both case studies, and we evaluate their effectiveness with seeded faults. Results show that the approach is effective at detecting over 88% of the seeded faults, while keeping the ratio of FPs at 4% or lower.European Union's Horizon 2020 Research and Innovation Programme (Grant Number: 871319)Junta de Andalucía US-1264651 (APOLO)Junta de Andalucía P18-FR-2895 (EKIPMENT-PLUS)Ministerio de Ciencia e Innovación RTI2018-101204-B-C21 (HORATIO)Mondragon Unibertsitatea IT1519-2

CNN-enabled Visual Data Analytics and Intelligent Reasoning for Real-time Optimization and Simulation: An Application to Occupancy-aware Elevator Dispatching Optimization

For most operational systems, the optimization problem is a combinatorial optimization problem, and the optimization performance largely determines the solution quality. Moreover, there exists a trade-off between the computing time of the decision-making process and the optimization performance, which is particularly evident in a system that conducts real-time operations. To obtain better solutions to the decision-making problem in a shorter time, many optimization algorithms are proposed to improve the searching efficiency in the search space. However, information extraction from the environment is also essential for problem-solving. The environment information not only includes the optimization model inputs, but also contains details of the current situation that may change the problem formulation and optimization algorithm parameter values. Due to the time constraint and the computation time of visual processing algorithms, most conventional operational systems collect environment data from sensor platforms but do not analyze image data, which contains situational information that can assist with the decision-making process. To address this issue, this thesis proposes CNN-enabled visual data analytics and intelligent reasoning for real-time optimization, and a closed-loop optimization structure with discrete event simulation to fit the use of situational information in the optimization model. In the proposed operational system, CNNs are used to extract context information from image data, like the type and the number of objects at the scene. Then reasoning techniques and methodologies are applied to deduct knowledge about the current situation to adjust problem formulation and parameter settings. Discrete event simulation is conducted to test the optimization performance of the system, and adjustments can be made to better fit situational information in the optimization process. To validate the feasibility and effectiveness, an application to occupancy-aware elevator dispatching optimization is presented.M.S

Design and Implementation of Embedded Based elevator Control System

The elevator control system is one of the important aspects in electronics control module in automotive application. Here elevator control system is designed with different levels. First the elevator control system is implemented for multi-storage building. This implementation is based on FPGA based Fuzzy logic controller for intelligent control of elevator group system. This proposed approach is based on algorithm which is developed to reduce the amount of computation required by focusing only on relevant rules and ignoring those which are irrelevant to the condition for better performance of the group of elevator system. Here only two inputs are considered i.e. elevator car distance and number of stops. Based on these data the fuzzy controller can calculate the Performance Index (PI) of each elevator car, the car which has maximum PI gives the answer to the hall calls. This would facilitate reducing the Average Waiting Time (AWT) of the passenger. In the second level, the dispatching algorithm is implemented for multi-storage building. Here six types of dispatching algorithms are considered. Based on the traffic situation and condition, one algorithm out of six is operated, that should reduce the Average Waiting Time of passenger and reduce the power consumption of elevator system. The hardware part of the work consists of a simple D. C. Motor, which can control the up and down movement of the elevator car. This D. C. Motor is controlled through the MC9S12DP256B microcontroller. Here four floor elevator systems have been considered and every floor has two switches, one switch is used for up movement and another switch is used for down movement. Based on the switch pressed, the elevator car can move either in upward or downward direction. Here two sensors are used in every floor. One sensor is used for detecting the elevator car when elevator car reached to its destination floor. This sensor detects the car and stops the D.C. Motor. At the same time, another sensor is used for opening and closing the door. Finally, a novel fuzzy based PID controller algorithm is implemented in the MC9S12dp256B microcontroller. This algorithm is mainly used for maintaining the constant speed of D.C. Motor with different load conditions

Modelling of a rope-free passenger transportation system for active cabin vibration damping

Conventional vertical passenger transportation is performed by lifts. Conventional traction-drive electrical lifts use ropes to transfer the rotational motion of an electrical motor into a vertical motion of the cabin. The vertical passenger transportation system discussed in this paper does not use any ropes, the motor directly provides a driving force, which moves the cabin. This new propulsion is realized through an electrical linear motor. The use of the linear motor requires a new design of the passenger transportation system (PTS), which includes reducing the weight of the car through lightweight construction. The reduced stiffness of the lightweight design renders the construction more vulnerable to vibrations. In order to improve ride quality of the transportation system it is necessary to develop new concepts to damp the vibrations. One way to increase stiffness characteristics of the system is to introduce active damping components to be used alongside passive damping components. It is essential to derive a dynamic model of the system in order to design and also later control these damping components in the best possible way. This paper describes the fundamental steps undertaken to derive a dynamic model for designing and controlling active damping components for the new type of vertical PTS. The model is derived as a Multi-Body System (MBS), where the connections between the bodies are modelled as spring damper elements. The derivation of the MBS is demonstrated on a transportation system, consisting of three main components: a sledge, holding the rotor of the linear motor; a mounting frame, which is used to provide support for the cabin; and the actual cabin. The modelling of the propulsion system, thus the electrical part of the PTS, will not be the focus of this work

Evaluating a holistic energy benchmarking parameter of lift systems by using computer simulation

At present, there are benchmarking parameters to assess the energy performance of lifts, e.g. one in Germany adopted by VDI (4707-1/2), one internationally published by ISO (BS EN ISO 25745-2:2015), and the other in Hong Kong adopted by The Hong Kong Special Administrative Region (HKSAR) Government. These parameters are mainly checking the energy consumed by a lift drive without considering real time passenger demands and traffic conditions; the one in Hong Kong pinpointing a fully loaded up-journey under rated speed and the two in Europe pinpointing a round trip, bottom floor to top floor and return with an empty car, though including energy consumed by lighting, displays, ventilation etc. A holistic normalization method by Lam et al [1] was developed a number of years ago by one of the co-authors of this article, which can assess both drive efficiency and traffic control, termed J/kg-m, which is now adopted by the HKSAR Government as a good practice, but not specified in the mandatory code. In Europe, the energy unit of Wh has been used but here, Joule (J), i.e. Ws, is adopted to discriminate the difference between the two concepts. In this article, this parameter is evaluated under different lift traffic scenarios using computer simulation techniques, with an aim of arriving at a reasonable figure for benchmarking an energy efficient lift system with both an efficient drive as well as an efficient supervisory traffic control

A study into the influence of the car geometry on the aerodynamic transient effects arising in a high rise lift installation

One of the main goals in designing a high-speed lift system is developing a more aerodynamically efficient car geometry that guarantees a good ride comfort and reduces the energy consumption. In this study, a three-dimensional computational fluid dynamics (CFD) model has been developed to analyse an unsteady turbulent air flow around two cars moving in a lift shaft. The paper is focused on transient aerodynamic effects arising when two cars pass each other in the same shaft at the same speed. The scenarios considered in the paper involve cars having three different geometries. Aerodynamic forces such as the drag force that occur due to the vertical opposite motions of the cars have been investigated. Attention is paid to the airflow velocity and pressure distribution around the car structures. The flow pattern in the boundary layer around each car has been calculated explicitly to examine the flow separation in the wake region. The results presented in the paper would be useful to guide the lift designers to understand and mitigate the aerodynamic effects arising in the lift shaft