Vernacular Patterns in Portugal and Brazil: Evolution and Adaptations

Traditional towns in Portugal and Brazil have evolved a finely tuned coordination between, on the one hand, modular dimensions for street widths and lot sizes, and on the other, a typology of room shapes and layouts within houses. Despite being well documented in urban history, this coordination was in the last century often interpreted as contingent, a result of the limited material means of pre-industrial societies. But the continued application and gradual adaptation of these urban and architectural patterns through periods of industrialization and economic development suggests that they respond both to enduring housing requirements and to piecemeal urban growth. This article surveys the persistence of urban and architectural patterns up to the early 20th century, showing their resilience in addressing modern housing and urbanization requirements.

Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

Many industrial sectors face increasing production demands and the need to reduce costs, without compromising the quality. The use of robotics and automation has grown significantly in recent years, but versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are excessive differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. Previous works have demonstrated the use of robot-manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized for a specific part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The novelty of this work lies in enabling the capability of mapping a part surface at the required level of sampling density, whilst minimizing the number of necessary view poses. Its development has also led to an efficient method of point cloud down-sampling and merging. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

Empirical relationships between algorithmic SDA-M-based memory assessments and human errors in manual assembly tasks

The majority of manufacturing tasks are still performed by human workers, and this will probably continue to be the case in many industry 4.0 settings that aim at highly customized products and small lot sizes. Technical systems could assist on-the-job training and execution of these manual assembly processes, using augmented reality and other means, by properly treating and supporting workers’ cognitive resources. Recent algorithmic advancements automatized the assessment of task-related mental representation structures based on SDA-M, which enables technical systems to anticipate mistakes and provide corresponding user-specific assistance. Two studies have empirically investigated the relations between algorithmic assessments of individual memory structures and the occurrences of human errors in different assembly tasks. Hereby theoretical assumptions of the automatized SDA-M assessment approaches were deliberately violated in realistic ways to evaluate the practical applicability of these approaches. Substantial but imperfect correspondences were found between task-related mental representation structures and actual performances with sensitivity and specificity values ranging from 0.63 to 0.72, accompanied by prediction accuracies that were highly significant above chance level.

Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

Many industrial sectors face increasing production demands and need to reduce costs, without compromising the quality. Whereas mass production relies on well-established protocols, small production facilities with small lot sizes struggle to update their highly changeable production at reasonable costs. The use of robotics and automation has grown significantly in recent years, but extremely versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are unavoidable differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. This could be avoided by measuring the real-geometry and the position of the specimen, which creates the paradox of having to plan robot paths for surface mapping purposes, before the originally intended robot task can be approached. Previous works have demonstrated the use of robotically manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized to the part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

Optimizing Lot-Sizes and Scheduling in Terms of Mass Customization

The goal of mass customisation is to offer products tailored to the specific needs of the customers. Even though customers are aware that manufacturers need a certain time to produce and deliver customised products, the companies might guarantee that their products will arrive on time. Then, the objective of manufacturing managers is to minimise the total flow time of parts through the shop. One of the effective ways to reach this objective is to optimise schedules in order to satisfy the due date criterion, which plays a crucial role in the mass customisation environment. This paper, in the first part, outlines methodological tools to tackle the problem of shortening delivery times through scheduling and management of resources. In the second part of the paper, the proposed methodology framework through the theoretical example is applied.

FAITH Software Life Cycle Model for Forex Expert Advisors

The emotional stress and uncertainties associated with foreign exchange (forex) trading due to the high risk of losing the investment capital has left most forex traders in a state of indecision on the best methodology to apply for achieving long term profit. The provision of lot sizes, leverages, take profits and stop losses in forex trading implies that very high profit can be made within a very short time with the same capital, but at the same time, very high losses can be incurred. On one hand, this provision often prompts a set of traders to become greedy by increasing their take profit levels, lot sizes and leverages, which in turn increases their probability of losing out. On the other hand, the provision creates doubts and induces the fear of losses in some other set of traders. Consequently, these set of conservative traders employ the use of relatively small lot sizes, low leverages and low values of take profit and high stop loss levels. This in turn often results in a devastating effect on the investment capital due to lost opportunities and resulting losses. The problem of losses in forex trading effort is compounded by the fact that many programmers and developers of forex expert advisors do not adopt a software life cycle, having learned only how to write codes to program the trading platform. Furthermore, software engineering professionals who understand the import of software development life cycles soon discover that conventional software life cycles are not capable of effectively handling the complexity of the forex market. This paper models the human characteristics of greed, fear and doubt as manifested by traders in forex trading using selected expert advisors’ properties. It proposes Facts, Analysis, Implementation, Testing and Hope (FAITH) software life cycle model for Forex trading profitability to tackle the problem of indecision in the development of forex expert advisors. The proposed model was implemented on a live trading platform for a period of three months and compared with doubt, fear and greed approach to trading. The results showed that while a level of greed can be profitable, FAITH software life cycle produced more profitable results and can be adopted for forex trading. Keywords: Software Development Life Cycle, Expert advisors, Forex Model, Losses, Profit

Industrial Assistance Systems to Enhance Human–Machine Interaction and Operator’s Capabilities in Assembly

In the context of digitalization and Industry 4.0, the world of work is changing comprehensively. Smaller lot sizes and increasing variability of products in the modern industrial production present new challenges for operators working in manual assembly. Industrial assistance systems help the worker during these production tasks to enhance their capabilities. The development of these systems is not only characterized by questions of the potential feasibility of new technical systems but also by the possibilities of a closer cooperation between humans and machines with the aim to synergize the outstanding abilities of humans with the special features of machines to bring together the best from both worlds. This chapter presents solutions for human–machine interaction and automation and delivers insight into different possibilities to enhance the various types of operator’s skills in industrial assembly. With this knowledge, each worker can be individually equipped with suitable supporting systems in order to be best prepared for future challenges in the daily production.