Movement Analytics: Current Status, Application to Manufacturing, and Future Prospects from an AI Perspective

Data-driven decision making is becoming an integral part of manufacturing companies. Data is collected and commonly used to improve efficiency and produce high quality items for the customers. IoT-based and other forms of object tracking are an emerging tool for collecting movement data of objects/entities (e.g. human workers, moving vehicles, trolleys etc.) over space and time. Movement data can provide valuable insights like process bottlenecks, resource utilization, effective working time etc. that can be used for decision making and improving efficiency. Turning movement data into valuable information for industrial management and decision making requires analysis methods. We refer to this process as movement analytics. The purpose of this document is to review the current state of work for movement analytics both in manufacturing and more broadly. We survey relevant work from both a theoretical perspective and an application perspective. From the theoretical perspective, we put an emphasis on useful methods from two research areas: machine learning, and logic-based knowledge representation. We also review their combinations in view of movement analytics, and we discuss promising areas for future development and application. Furthermore, we touch on constraint optimization. From an application perspective, we review applications of these methods to movement analytics in a general sense and across various industries. We also describe currently available commercial off-the-shelf products for tracking in manufacturing, and we overview main concepts of digital twins and their applications

Planning Practical Paths in High-Dimensional Space

Unlike traditional manipulator robots which tend to have small numbers of degree of freedom (DOF), tentacle robots utilize redundant DOFs in order to enhance their ability to deal with complex environments and tasks. However, it also makes the planning and control of such devices extremely difficult. One of the fundamental tasks robots have to perform is planning their motions while avoiding collisions with obstacles in the environment, which is known to be PSPACE-complete in the robot's DOF. As a consequence heuristic sampling-based approaches have been developed to solve high-dimensional real-world path planning problems. A shortcoming of the current sampling-based algorithms is that they can obtain highly non-optimal solutions since they rely upon randomization to explore the search space. Although these planners may find a valid solution, the solutions found are often not practical in that they do not take into account soft application-specific constraints. This thesis integrates soft constraints in addition to the basic geometric or hard constraints in the general path planning process for high DOF robots. The practicality of paths are formulated based on the notion of soft constraints found in the Planning Domain Definition Language 3 (PDDL3). A range of optimization strategies are developed targeted towards user-preferred qualities by integrating soft constraints in the pre-processing (i.e. sampling), planning and post-processing phases of the sampling-based path planners. An auction-based resource allocation approach coordinates competing optimization strategies. This approach uses an adaptive bidding strategy for each optimizer and in each round the optimizer with the best predicted performance is selected. This general coordination system allows for flexibility in both the number and types of the optimizers to be used. Experimental validation with real and simulated tentacle robots demonstrate the effectiveness of the approach

TOWARDS SUSTAINABLE AUTONOMOUS VEHICLES

Ph.DDOCTOR OF PHILOSOPH

Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling

In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the forefront. Nevertheless, the recent pandemic, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects. There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the COVID-19 pandemic has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects

Smoking and Second Hand Smoking in Adolescents with Chronic Kidney Disease: A Report from the Chronic Kidney Disease in Children (CKiD) Cohort Study

The goal of this study was to determine the prevalence of smoking and second hand smoking [SHS] in adolescents with CKD and their relationship to baseline parameters at enrollment in the CKiD, observational cohort study of 600 children (aged 1-16 yrs) with Schwartz estimated GFR of 30-90 ml/min/1.73m2. 239 adolescents had self-report survey data on smoking and SHS exposure: 21 [9%] subjects had “ever” smoked a cigarette. Among them, 4 were current and 17 were former smokers. Hypertension was more prevalent in those that had “ever” smoked a cigarette (42%) compared to non-smokers (9%), p\u3c0.01. Among 218 non-smokers, 130 (59%) were male, 142 (65%) were Caucasian; 60 (28%) reported SHS exposure compared to 158 (72%) with no exposure. Non-smoker adolescents with SHS exposure were compared to those without SHS exposure. There was no racial, age, or gender differences between both groups. Baseline creatinine, diastolic hypertension, C reactive protein, lipid profile, GFR and hemoglobin were not statistically different. Significantly higher protein to creatinine ratio (0.90 vs. 0.53, p\u3c0.01) was observed in those exposed to SHS compared to those not exposed. Exposed adolescents were heavier than non-exposed adolescents (85th percentile vs. 55th percentile for BMI, p\u3c 0.01). Uncontrolled casual systolic hypertension was twice as prevalent among those exposed to SHS (16%) compared to those not exposed to SHS (7%), though the difference was not statistically significant (p= 0.07). Adjusted multivariate regression analysis [OR (95% CI)] showed that increased protein to creatinine ratio [1.34 (1.03, 1.75)] and higher BMI [1.14 (1.02, 1.29)] were independently associated with exposure to SHS among non-smoker adolescents. These results reveal that among adolescents with CKD, cigarette use is low and SHS is highly prevalent. The association of smoking with hypertension and SHS with increased proteinuria suggests a possible role of these factors in CKD progression and cardiovascular outcomes

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen