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The Leeds Autism Diagnostic Service (LADS) is an all IQ service accepting professional and self-referrals, from age 18, for diagnostic assessment. LADS is unusual compared to other diagnostic services in England, in that it accepts self-referrals. The purpose of this paper is to compare diagnostic outcome between self-referrals and other referral sources.

This is a service evaluation of all 692 referrals for diagnostic assessment into LADS, over a three year period, from 2016 to 2018. The diagnostic outcomes were compared between self-referrals and other referral sources. Secondary analysis looked at age and gender differences between these groups.

There were 98 self-referrals over three years with autism diagnosed in 65 per cent. In total, 594 other referrals were received during this time period, with autism diagnosed in 44 per cent. This showed a significant difference of 21 per cent with 95% confidence intervals of 10–31 per cent (p=0.0001) using a n−1 χ² test. In total, 59 per cent of self-referrals were from patients identifying as female, which compared to 35 per cent identifying as female from other referrals. This was a difference of 24 per cent with 95% confidence interval of 14–34 per cent (p<0.0001) on the n−1 χ² test.

Factors which may influence the ability to generalise from these results are: that LADS covers a large mainly urban and suburban area with a range of ethnic and socioeconomic diversity; that LADS is an all IQ service unlike some other autism diagnostic services; historical and service-related factors unique to Leeds may be dissimilar to other locations. It was beyond the scope of this evaluation to perform a qualitative analysis to compare the referral sources, but this may be an area for further study.

This evaluation supports the use of a self-referral route for adult autism diagnostic services on a local level and may support its use more widely in other services.

This evaluation, in demonstrating proportionately significantly higher autism diagnosis from self-referrals is likely to be reducing the work load of professionals who would normally make referrals. Alternatively, it may be capturing a subgroup of the autism population who would not otherwise have sought diagnosis. In either scenario, it supports and is consistent with a patient centred approach to accessing appropriate diagnostic services.

The authors are not aware that any previous evaluation of this nature has been conducted and feel this evaluation supports the use of a self-referral pathway in adult autism diagnostic services.

Purpose: This chapter aims to analyse and highlight the current landscape of performance management (PM) systems, and the benefits of integrating modern technology such as smart analytics (SA) and artificial intelligence (AI) into PM systems. The chapter discusses the application of AI in PM tasks which successively simplify many offline PM tasks.

Methodology: To carry out this analysis, a systematic literature review was performed. The review covers literature detailing PM components as well as research concerned with the integration of SA and AI into PM systems.

Findings: This study uncovers the merits of using SA and AI in PM. SA technology provides organisations with a clear direction for improvement, rather than simply state failure in performance. AI can be used to automate redundant tasks while retaining the human element of decision-making. AI also helps reduce the time required to take action on feedback.

Significance: The findings of this research provide insights into the use of SA and AI to make PM tasks fast, scalable, and error-free.

The purpose of this paper is to provide a holistic view of the link between the identification of complexity contributing factors, the application of project management approaches and their impacts on the performance of Information Technology (IT)-enabled change projects.

A qualitative approach of an embedded single-case design comprising three IT-enabled change projects delivered in Australia was used to explore the impact of complexity contributing factors and project management approaches on project performance measures. Semi-structured interviews were used as the main data collection method. Thematic analysis was used as the data analysis approach.

The results from the thematic analysis highlight that complexity contributing factors are related to two categories of complexity defined in this paper: technical uncertainties and uncertainty in goals and deliverables, both have an impact on the performance of IT-enabled change projects. It also highlights key project management approaches such as the use of an adaptive management approach and good communication as key to managing complexity. It also identifies a misalignment between stakeholder perception of success and the project management success measure for complex IT-enabled projects.

The research is based on data collected from Australian participants involved in three case studies. Additional data collection and reviews from practitioners in the field of project management could further refine and improve this research.

The research facilitates the identification of specific complexity contributing factors at the early stage of a project to ensure that the appropriate project management approaches and success measures are used.

The paper contributes to rethinking the pathways towards improving project performance in the IT sector by expanding the identification of project complexity to understanding how complexity and the management approaches impact project performance.

This paper's objective is to explain the concept of proper kinematic constraint to guide requirements‐driven design of mechanical assemblies and to connects proper constraint to the datum flow chain (DFC) and key characteristics (KCs).

The paper presents proper constraint as a way to support the goal of placing key parts in particular geometric relationships with respect to one another so that a DFC can deliver KCs unambiguously. Such a DFC is said to be competent. Additionally, a competent DFC is robust in the sense that the constraint relationships between parts retain their definition and effect under all allowed variations in parts.

Failure to provide proper constraint can lead to undesired consequences including locked‐in stresses and difficult or inconsistent assembly. Some designs need to be over‐constrained, and this requires very careful control and tight tolerances on the over‐constrained degrees of freedom in order to avoid or at least understand the consequences listed above.

Mathematical methods exist to test designs for proper constraint. The simplest, and occasionally unsuccessful, is the Kutzbach criterion. Screw theory is the most reliable method but its application requires extra knowledge and mathematical tools.

Most CAD software and tolerance analysis software do not test designs for their state of constraint. The engineer needs to take account of this independently and be aware of the limitations of software as a guide. Tolerance analysis software that does not take account of constraint may yield incorrect answers.

The paper reinvigorates a once‐well‐known principle and makes engineers aware of it. It also links this concept to the concepts of DFC and KCs and supports a mathematically‐based method for designing assemblies.

Products are complex and are comprised of many parts from many sources, designed at different times by different people and companies. The same holds true for the tooling and fixtures used to make and assemble them. There is little research and practice on how to design assemblies that deal with such problems. The purpose of this paper is to describe a technique aimed at this goal.

The technique is built up from a number of concepts. The paper defines the intent of the design, identifies key assembly‐level dimensions called key characteristics (KCs) that embody the intent, designs an architecture for the assembly that will deliver each key dimension within some stated tolerance, and conveys the intent and architecture in the form of a diagram called a datum flow chain (DFC).

The design and achievement of KCs is a joint responsibility of engineering and manufacturing.

The DFC method provides people with a vocabulary and a simple diagramming technique by which they can document the design intent, debate the merits of different designs, and anticipate where assembly problems will occur.

The purpose of this paper is to present the methodology and the results on the design and development of an autonomous, golf ball picking robot, for driving ranges.

The strategy followed to develop a commercial product is presented, based on prior identification requirements, which consist of picking up golf balls on a driving range in a safe and efficient way.

A fully working prototype robot has been developed. It uses two driving wheels and a third cast wheel, and pushes a standard gang which collects the balls from the ground. A hybrid information system was implemented in order to provide a statistically relevant prediction of golf balls location, to optimize the path the robot has to follow in order to reduce time and cost. Autonomous navigation was developed and tested on a simulation environment.

Preliminary results showed that the new path planning algorithm Twin‐RRT* is able to form closed loop trajectories and improve the result over time. Kinematic constraints were already taken into account on the algorithm. This sampling based algorithm has potential usage in solving other TPP (Travelling Purchaser Problem) related problems.

The prototype feasibility is being tested in real driving ranges. It has autonomy of up to 8 h per day. It is capable of collecting up to 1,200 balls in one single journey. It weighs 130 kg and is capable of climbing slopes of up to 22°. The maximum speed is 8 km/h and the robot takes 140 min to completely sweep a 25,000 m² field at 7.2 km/h (2 m/s) average speed.

There are about 30,000 golf practice fields, of which 18,000 are located in the USA and Canada. In some countries the golf industry represents more than 15 per cent of tourism GNP. In a typical practice field, about 10,000 balls have to be picked up every day.

An important contribution of this paper is the algorithm for path planning in order to optimize the ball pick up task, reducing time and cost. There are two patents are pending concerning the technological novelties of this work.

A new system of leasing robots to industry with aid of funds from both small and large banks appears to be attracting little interest from Japanese industry. The system does, however, offer potential for British industry short of funds to invest in new plant and equipment.

Fast automatic assembly of fuel gauges is just one of the many advances the Japanese are making in automated assembly, as John Hartley indicates in his report from the Tokyo International Conference on Production Engineering.

This paper aims to explore the use of the knowledge management (KM) perspective for configuration projects. Configuration projects implement configurators as information technology systems that help companies manage the specification process of customised products. An effective method of retrieving and formalising knowledge for configurators is essential, because it can reduce the risk of unsuccessful implementation and the time and effort required for development. Unfortunately, no standard KM frameworks are available specifically for configuration projects. This study identifies the knowledge necessary for different phases of a configuration project (which knowledge, for what purpose and from what sources), examines how it is transformed during a configuration project (what KM activities and tools are used) and establishes how the knowledge can be documented for future maintenance and updates.

This paper proposes a four-step framework for making the KM process more efficient in configuration projects. The framework is based on the literature, developed in collaboration with industrial partners and tested on four configuration projects in two engineering companies. The framework is a structured KM approach designed to save time for both domain experts and the configuration team. The authors have used a qualitative exploratory design based on multiple data sources: documentation, workshops and participant observation.

The proposed framework comprises four steps: determination of the system’s scope, to establish the project’s goal based on stakeholders’ requirements and prioritise the required products and processes; knowledge acquisition, to classify the knowledge according to the desired output and identify different knowledge sources; modelling and knowledge validation; and documentation and maintenance, to ensure that the KM system can be maintained and updated in the future.

Because the framework is tested on a limited number of cases, its generalisability may be limited. However, focusing on a few case applications allows us to assess the effectiveness of the framework in detail and in depth to identify the practical challenges of applying it. The results of the tests support the framework’s validity. Although the framework is designed mainly for engineering companies, other industries could benefit from using it as well.

The individual steps of the framework create a structured approach for the KM process. Thus, the approach can save both time and resources for companies, without the need for additional investment.

A standard framework is lacking in the literature on KM for configuration projects. This study fills that gap by developing a KM framework for configuration projects, based on KM frameworks developed for IT projects, and KM tools.