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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 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.

Simple and affordable systems are described to assist wheelchair users in steering their wheelchairs across sloping ground. The systems can be attached to many standard powered wheelchairs. Wheelchairs often steer by having two swivelling caster wheels but problems with this configuration occur when a wheelchair is driven along sloping ground because the casters can swivel in the direction of the slope. Gravity then causes the wheelchair to start an unwanted turn or ‘veer’ and the chair goes in an unintended direction. This situation is exacerbated for switch users, as switches cannot provide fine control to trim and compensate. Early experiments demonstrated that calibrating wheelchair controllers for straight‐line balance and optimising motor‐compensation did not solve this problem. Caster angle was selected to provide feedback to the wheelchair controllers. At the point when veer is first detected, a wheelchair has already begun to alter course and the job of the correction system is to minimise this drift from the desired course. A rolling road was created as an assessment tool and trials with both the test bed and in real situations were conducted to evaluate the new systems. The small swivel detector that was created could be successfully attached to caster swivel bearings. The new system was successful, robust and was not affected by changeable parameters. Although primarily intended for switch users, the methods can be applied to users with proportional controls.

The purpose of this paper is to present powered‐wheelchair transducers and systems that provide more control, reduced veer on slopes, and improved energy conservation, while reducing effort. They are especially significant for people with movement disorders who lack sufficient hand‐grasp and release ability or sufficient targeting skill to use joysticks.

Laboratory test rigs are created to test proportional switches and teach potential users. Then, trials are conducted with a rolling road and in real situations. Caster angle‐measurement is selected to provide feedback to minimize drift away from a chosen course and an electronic solution was created to match driver control to caster‐steering‐position. A case study is described as an example.

Results and advantages are presented from changing from using a set of digital‐switches to a set of new variable‐switches and then adding a sensor system to prevent veer on slopes. Systems have been tested for nearly two years and shown to assist powered‐wheelchair‐users with poor targeting skills.

The research used wheelchairs with caster‐wheels but the systems could easily be used on other wheelchairs.

Simple input‐devices are presented that isolate gross motor function and are tolerant to involuntary movements (proportional‐switches). A sensor system is presented that assists users in steering across sloping or uneven ground.

Proportional‐switches and sensors are shown to reduce veer and provide more control over turn and forward speed and turn radius while reducing frustration and improving energy conservation. The simple and affordable systems could be created and attached to many standard powered‐wheelchairs in many organisations.

The purpose of this paper is to present a multi‐expert system that can provide designers with suggestions for improvement. The multi‐expert system can analyse a design and provide designers with ideas for changes to designs at an early stage in order to improve assembly later in the manufacturing process.

The whole system consists of four expert systems: computer‐aided design (CAD) expert, automated assembly expert, manual assembly expert and design analysis expert. The design analysis expert includes a sub‐system to collate the information from the assembly experts and to provide costs and advice.

The paper finds that the approach and the systems can reduce manufacturing costs and lead times.

A knowledge‐based reckoning approach to design‐for‐assembly automation is used. The approach and systems can reduce manufacturing costs and lead times. The system can estimate assembly time and cost for manual or automatic assembly and select suitable assembly techniques.

The system can estimate assembly time and cost for manual or automatic assembly and select a suitable assembly technique.

The new system models assembly, product and process design using a natural approach for capturing intelligence. The new approach categorised automated assembly and manual assembly into separate individual experts. Intelligence and knowledge from each is captured and embedded within the individual expert that represented the process. This approach enabled greater flexibility and made the sub‐systems easier to modify, upgrade, extend and reuse.

The purpose of this paper is to investigate the effect of time delay on the ability of a human operator to complete a task with a teleoperated mobile‐robot using two systems, two different ways of interacting with the mobile‐robots and several different environments.

Teleoperators are observed completing a series of tasks using a joystick to control a mobile‐robot while time delays are introduced to the system. They sit at a computer and view scenes remotely on a screen. Cameras are either mounted on the robot or mounted externally so that they view both the environment and robot. Teleoperators complete the tests both with and without sensors. One robot system uses an umbilical cable and one uses a radio link.

In simple environments, a teleoperator may perform better without a sensor system to assist them but as time delays are introduced then there are more failures. In more complicated environments or when time delays are longer, then teleoperators perform better with a sensor system to assist. Teleoperators may also tend to perform better with a radio link than with an umbilical connection.

Teleoperated systems rely heavily on visual feedback and experienced operators. This paper investigates the effect of introducing a delay to the delivery of that visual feedback.

The paper suggests that in simple environments with short time delays then the amount of sensor support should be small but in more complicated environments or with longer delays then more sensor support needs to be provided.

Results from imposing time delays on a teleoperated mobile‐robot are presented. Effects on the task of different ways of viewing activity on a computer display are presented, that is with cameras mounted on the robot or cameras mounted externally to view both the environment and robot. Results from using sensors to assist teleoperators are presented. The paper suggests that the amount of sensor support should be varied depending on circumstances.

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.

This paper presents new prototype powered wheelchair systems that are easy to use and safe. The systems use simple ultrasonic sensor systems to assist users in steering their powered wheelchairs. The new systems could improve the chances of some disabled children learning that behaviour and interaction with the environment can be controlled. An overview of the benefits to be offered by an automated wheelchair is included. Some results, problems and difficulties are described along with an assessment of the current position and the way forward.