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The paper aims to propose a system that uses a combination of techniques to suggest weld requirements for ships parts. These suggestions are evaluated, decisions are made and then weld parameters are sent to a program generator.

A pattern recognition system recognizes shipbuilding parts using shape contour information. Fourier‐descriptors provide information and neural networks make decisions about shapes.

The system has distinguished between various parts and programs have been generated so that the methods have proved to be valid approaches.

The new system used a rudimentary curvature metric that measured Euclidean distance between two points in a window but the improved accuracy and ease of implementation can benefit other applications concerning curve approximation, node tracing, and image processing, but especially in identifying images of manufactured parts with distinct corners.

A new proposed system has been presented that uses image processing techniques in combination with a computer‐aided design model to provide information to a multi‐intelligent decision module. This module will use different criteria to determine a best weld path. Once the weld path has been determined then the program generator and post‐processor can be used to send a compatible program to the robot controller. The progress so far is described.

This paper aims to examine the two different approaches adopted in the UK to regulate directors’ remuneration. The paper also aims to explore the two approaches to understand which one better regulates directors’ pay and why. It provides an account of the two approaches’ evolution, effectiveness and challenges towards the regulation of directors’ remuneration. The paper will also make some recommendations on both approaches and the way forward to better regulate directors’ remuneration.

The paper reviews various corporate governance codes, its recommendations on directors’ remuneration, its effectiveness and the challenges it face in regulating directors’ remuneration. The paper also reviews provisions of the Companies Act 2006 on directors’ remuneration, its effectiveness and challenges faced.

The paper finds that corporate governance adopts a better approach to regulating directors’ pay than the Companies Act 2006 because it targets the pay setting process. However, the existence of grey areas and lack of enforcement procedure poses a challenge on its effectiveness. The Companies Act 2006 is unable to regulate directors’ pay adequately because it adopts a corrective approach and it considers directors’ remuneration as a management responsibility.

The paper offers an up-to-date assessment of the two approaches to regulating directors’ pay in the UK. It highlights the challenges faced by both approaches and which approach could regulate directors pay better and its challenges. The paper further makes recommendations on how the regulation of directors’ remuneration can be effective in the UK.

This paper aims to describe research work to create an innovative, and intelligent solution for energy efficiency optimisation.

A novel approach is taken to energy consumption monitoring by using ambient intelligence (AmI), extended data sets and knowledge management (KM) technologies. These are combined to create a decision support system as an innovative add-on to currently used energy management systems. Standard energy consumption data are complemented by information from AmI systems from both environment-ambient and process ambient sources and processed within a service-oriented-architecture-based platform. The new platform allows for building of different energy efficiency software services using measured and processed data. Four were selected for the system prototypes: condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase, and continuous improvement/optimisation of energy efficiency.

An innovative and intelligent solution for energy efficiency optimisation is demonstrated in two typical manufacturing companies, within one case study. Energy efficiency is improved and the novel approach using AmI with KM technologies is shown to work well as an add-on to currently used energy management systems.

The decision support systems are only at the prototype stage. These systems improved on existing energy management systems. The system functionalities have only been trialled in two manufacturing companies (the one case study is described).

A decision support system has been created as an innovative add-on to currently used energy management systems and energy efficiency software services are developed as the front end of the system. Energy efficiency is improved.

For the first time, research work has moved into industry to optimise energy efficiency using AmI, extended data sets and KM technologies. An AmI monitoring system for energy consumption is presented that is intended for use in manufacturing companies to provide comprehensive information about energy use, and knowledge-based support for improvements in energy efficiency. The services interactively provide suggestions for appropriate actions for energy problem elimination and energy efficiency increase. The system functionalities were trialled in two typical manufacturing companies, within one case study described in the paper.

This paper aims to describe real time improvements to the performance and trajectories of robots for which paths had already been planned by some means, automatic or otherwise. The techniques are applied to industrial robots during the gross motions associated with pick and place tasks. Simple rules for path improvement are described.

The dynamics of the manipulator in closed form Lagrange equations are used to represent the dynamics by a set of second‐order coupled non‐linear differential equations. The form of these equations is exploited in an attempt to establish some simple rules. Sub‐optimal paths are improved by considering simple rules developed from the model of the machinery dynamics. By considering the physical limitations of the manipulator, performance was improved by refining pre‐calculated paths. Experiments were performed with a prototype robot and an old Puma 560 robot in a laboratory environment. Once the method had been tested successfully then experiments were conducted with a Kuka KR125 Robot at Ford Motor Company. The measured quantities for all the robots were drive currents to the motors (which represented the torques) and the joint angular positions.

The method of path refinement presented in this paper uses a simplified model of the robot dynamics to successfully improve the gross motions associated with a pick and place task. The advantage of using the input‐output form described was that intermediate non‐linearities (such as gear friction) and the motor characteristics were directly incorporated into the model.

Even though many of the theoretical problems in manipulator dynamics have been solved, the question of how to best apply the theories to industrial manipulators is still being debated. In the work presented in this paper, information on system dynamics is used to produce simple rules for “path improvement”.

Most fast algorithms are for mobile robots and algorithms are scarcer for manipulators with revolute joints (the most popular type of industrial robot). This work presents real time methods that allow the robot to continue working while new global paths are automatically planned and improved as necessary.

Motion planning for manipulators with many degrees of freedom is a complex task and research in this area has been mostly restricted to static environments, offline simulation or virtual environments. This research is applied in real time to industrial robots with revolute joints.

The purpose of this paper is to investigate how to make tele‐operated tasks easier using an expert system to interpret joystick and sensor data.

Current tele‐operated systems tend to rely heavily on visual feedback and experienced operators. Simple expert systems improve the interaction between an operator and a tele‐operated mobile‐robot using ultrasonic sensors. Systems identify potentially hazardous situations and recommend safe courses of action. Because pairs of tests and results took place, it was possible to use a paired‐samples statistical test.

Results are presented from a series of timed tasks completed by tele‐operators using a joystick to control a mobile‐robot via an umbilical cable. Tele‐operators completed tests both with and without sensors and with and without the new expert system and using a recently published system to compare results. The t‐test was used to compare the means of the samples in the results.

Time taken to complete a tele‐operated task with a mobile‐robot partly depends on how a human operator interacts with the mobile‐robot. Information about the environment was restricted and more effective control of the mobile‐robot could have been achieved if more information about the environment had been available, especially in tight spaces. With more information available for analysis, the central processor could have had tighter control of robot movements. Simple joysticks were used for the test and they could be replaced by more complicated haptic devices. Finally, each individual set of tests was not necessarily statistically significant so that caution was required before generalising the results.

The new systems described here consistently performed tasks more quickly than simple tele‐operated systems with or without sensors to assist. The paper also suggests that the amount of sensor support should be varied depending on circumstances. The paired samples test was used because people (tele‐operators) were inherently variable. Pairing removed much of that random variability. When results were analysed using a paired‐samples statistical test then results were statistically significant. The new systems described in this paper were significantly better at p<0.05 (95 per cent probability that this result would not occur by chance alone).

The paper shows that the new system performed every test faster on average than a recently published system used to compare the results.

This paper aims to explore the development and application of place crowd safety management tools for areas of public assembly and major events, from a practitioner perspective.

The crowd safety risk assessment model is known as design, information, management-ingress, circulation, egress (DIM-ICE) (Still, 2009) is implemented to optimise crowd safety and potentially throughput. Three contrasting case studies represent examples of some of the world’s largest and most challenging crowd safety projects.

The paper provides some insight into how the DIM-ICE model can be used to aid strategic planning at major events, assess potential crowd risks and to avoid potential crowd safety issues.

It provides further clarity to what effective place management practice is. Evidence-based on the case studies demonstrates that the application of the DIM-ICE model is useful for recognising potential place crowd safety issues and identifying areas for require improvement.

Crowd science is an emerging field of research, which is primarily motivated by place crowd safety issues in congested places; the application and reporting of an evidence-based model (i.e. DIM-ICE model) add to this. The paper addresses a research gap related to the implementation of analytic tools in characterising place crowd dynamics.

This paper aims to review seven artificial intelligence tools that are useful in assembly automation: knowledge‐based systems, fuzzy logic, automatic knowledge acquisition, neural networks, genetic algorithms, case‐based reasoning and ambient‐intelligence.

Each artificial intelligence tool is outlined, together with some examples of their use in assembly automation.

Artificial intelligence has produced a number of useful and powerful tools. This paper reviews some of those tools. Applications of these tools in assembly automation have become more widespread due to the power and affordability of present‐day computers.

Many new assembly automation applications may emerge and greater use may be made of hybrid tools that combine the strengths of two or more of the tools reviewed in the paper. The tools and methods reviewed in this paper have minimal computation complexity and can be implemented on small assembly lines, single robots or systems with low‐capability microcontrollers.

It may take another decade for engineers to recognize the benefits given the current lack of familiarity and the technical barriers associated with using these tools and it may take a long time for direct digital manufacturing to be considered commonplace… but it is expanding. The appropriate deployment of the new AI tools will contribute to the creation of more competitive assembly automation systems.

Other technological developments in AI that will impact on assembly automation include data mining, multi‐agent systems and distributed self‐organising systems.

The novel approaches proposed use ambient intelligence and the mixing of different AI tools in an effort to use the best of each technology. The concepts are generically applicable across all industrial assembly processes and this research is intended to prove that the concepts work in manufacturing.