Design requirements for SRB production control system. Volume 5: Appendices

A questionnaire to be used to screen potential candidate production control software packages is presented

QUALITY AND PRODUCTIVITY IMPROVEMENTS IN ADDITIVE MANUFACTURING

Additive manufacturing (AM) is a relatively new manufacturing technology compared to the traditional manufacturing methods. Even though AM processes have many advantages, they also have a series of challenges that need to be addressed to adapt this technology for a wide range of applications and mass production. AM faces a number of challenges, including the absence of methods/models for determining whether AM is the best manufacturing process for a given part. The first study of this thesis proposes a framework for choosing specific AM processes by considering the complexity level of a part. It has been proven that the method works effectively through numerical experiments. Optimization of process parameters through expensive and time-consuming experiments is another issue with AM. To address this issue, an empirical model is presented in the second study to optimize parameters for minimizing building costs through maximizing the trade-off between productivity and quality. The proposed model proves to be effective in reducing building costs at any quality level. The results indicate that process parameters can be optimized quickly and accurately, as compared to the time-consuming and expensive experimental methods. Another limitation of AM is the lack of capability to use multiple materials, which is a concern when adapting this technology to mass production. To address this issue, a new scheduling model with considering multi-material types is introduced in the third study. Based on the numerical results, the proposed model can provide optimal sequence by maximizing the trade-off between tardiness and material switching cost

Feasibility study of an Integrated Program for Aerospace-vehicle Design (IPAD) system. Volume 2: Characterization of the IPAD system, phase 1, task 1

The aircraft design process is discussed along with the degree of participation of the various engineering disciplines considered in this feasibility study

A Study of Defense Logistics Agency Inventory Classifications: Application of Inventory Control Methods to Reduce Total Variable Cost and Stockage Levels

This thesis analyzes the financial impact of applying a single inventory requirements model to three separate classes of inventory at the Defense Logistics Agency\u27s (DLA) Defense Supply Center-Columbus (DSCC) commodity management facility. DLA\u27 5 blanket application of its variation of the Economic Order Quantity (EOQ) requirements model may not be appropriate for all levels of demand, possibly suboptimizing DLA\u27s desire to minimize inventory costs while still providing an appropriate level of customer service. Simulation analyses of the DLA EOQ requirements model, the Silver-Meal heuristic, and Periodic Order Quantity models were conducted to examine which dynamic lot-sizing model is more effective in minimizing inventory costs and levels for different levels of item demand. The Periodic Order Quantity model provided lower inventory levels and total variable costs than the DLA EOQ and the Silver-Meal models for the medium demand category. The DLA EOQ requirements model was found to provide lower inventory levels and total variable costs than either the POQ or the Silver-Meal models in the low and high demand categories

Workload Control in Additive Manufacturing Shops where Post-Processing is a Constraint:An Assessment by Simulation

Additive Manufacturing (AM) shops typically produce high variety, low volume products on a to-order basis. Products are first created in parallel batches at a single AM station before being subjected to several post-processing operations. While there exists an emerging literature on AM station scheduling and order book smoothing, this literature has largely neglected downstream post-processing operations, which also affect overall performance. Workload Control provides a unique production control solution for these post-processing operations, but the specific AM shop structure has been neglected in the literature. Using simulation, this study shows that load balancing via the use of workload norms, as is typical for Workload Control, becomes ineffective since the norm must allow for the operation throughput time at the AM station and for its variability. A sequencing rule for the jobs waiting to be released that inherently creates a mix of jobs that balances the workload is therefore identified as the best-performing rule. These findings reinforce the principle that load limiting should be used at upstream stations whereas sequencing should be applied at downstream stations. Finally, although the focus is on AM shops, the findings have implications for other shops with similar structures, e.g. in the steel and semi-conductor industries

The design and formative evaluation of computer based qualitative modelling environments for schools

This research investigated how computers might enable young learners to build models so that they can express and explore their ideas and hence they can gain understanding of the subject matter as well as developing modelling abilities. A design for a qualitative modelling environment was produced, which incorporated a simple rule-based metaphor that could be presented as a diagram. The design was founded on empirical evidence of children modelling as well as theoretical grounds. This research originated in and contributed to the Modus Project, a joint venture between King's College London and the Advisory Unit for Microtechnology in Education, Hertfordshire County Council. A prototype of the software, Expert Builder, was implemented by software engineers from the Modus team. The initial stage of evaluation, based on a questionnaire survey and widespread trialling, established that the tool could be used in a wide range of educational contexts. A detailed study of children using the qualitative modelling environment was conducted in three primary schools involving 34 pupils, aged nine to 11. They used the modelling environment within the classroom in their normal curriculum work over one school year on a variety of topics assisted by their class teacher. The modelling environment enabled cooperative groupwork and supported pupils in consolidating and extending their knowledge. A formative evaluation was used to inform the design of a revised version of the software. In addition the experiences of children using the software were analysed. A framework was developed which characterised the stages in the modelling process. Teachers in the study were observed to demonstrate the earlier stages of the modelling process and then to set tasks for the children based on the later stages of building and testing the models. The evidence suggested that the abilities to model were context dependent so that pupils as young as nine years old could undertake the whole modelling process provided that they were working on subject matter with which they were familiar. The teachers made use of computer based modelling in order to develop and reinforce pupils' understanding of various aspects of the curriculum and therefore they chose modelling tasks for the children. However in one school the children were given the opportunity to design and build models of their own choice and they demonstrated that they were able to carry out all the stages in the modelling process. A taxonomy of computer based modelling is proposed which could be used to inform decisions about the design of the modelling curriculum and could provide a basis for researchers investigating the modelling process. This would be useful for further research into the intellectual and social activities of people learning to model and for teachers seeking to develop a framework for the modelling curriculum. The National Curriculum (Department of Education and Science and the Welsh Office, 1990) specifies that early steps in computer based modelling should involve exploring models developed by others and pupils are not required to build models themselves until level 7 which is expected to be reached by more able 14 year-olds. In this thesis it is argued that a modelling curriculum should provide early opportunities for pupils to undertake the modelling process by developing simple models on familiar subject matter as well as opportunities for exploring more complex models as evidence from research reported in this thesis suggests that younger pupils are able to build models. In this way pupils will be enabled to acquire modelling capability as well as developing their understanding of a range of topics through modelling. Progression in modelling capability would involve constructing models of more complex situations and using a wider range of modelling environments

Data-driven review of additive manufacturing on supply chains: Regionalization, key research themes and future directions

Additive manufacturing (AM) has the potential to greatly impact supply chains in a number of positive ways, particularly in regional and remote locations. This study aimed to identify the impact and application of AM on regional supply chains (RSCs) and address the associated challenges while promoting the sustainable use of this technology. Therefore, this study implemented a streamlined evaluation text mining method that employed Latent Dirichlet Allocation (LDA)-based modeling for robust content analysis. Over the past 19 years (2004–2022), there has been a significant increase in the number of journal articles that center on AM in supply chains. Through an extensive analysis of 341 published papers, five main research themes were identified: manufacturing, environment, costs, logistics, and maintenance. The identification of a gap in research in regional locations is significant as they often face unique challenges in their supply chains, such as limited access to technology and required infrastructure and the availability of resources. These challenges may have a different impact on the implementation of AM. Further, the possible impact of using AM in the recovery of RSCs after the COVID-19 pandemic is substantial and can bring about several positive sustainable changes, including increased responsiveness to changing demands, shorter production lead times, lower material usage and waste, customizability, localized production, energy efficiency, and reduced carbon dioxide and gas emissions

Development of a business model for diagnosing uncertainty in MRP environments

Over the last thirty years, Materials Requirements Planning (MRP) based systems have become commonplace within batch manufacturing environments, but are still widely held to be under performing. This research hypothesises that there may be inherent problems associated with the application due to uncertainties that exist within dynamic operating environments. Research has highlighted both the absence of any business model that uses a structured and systematic approach to deal with uncertainty holistically and the lack of any widely used, consistent performance measures to allow comparison of research results. The industrial need for such a holistic approach became apparent from survey work, which showed MRP under-performed in the presence of uncertainty even when numerous Buffering and Dampening (BAD) approaches were applied. A business model of uncertainty that structures the causes and effects of uncertainty as a hierarchy of four levels has been proposed, to be verified and validated through industrial survey and simulation respectively. The relationship between causes and effects in the business model has been verified from survey results using Analysis of Variance (ANOVA), which identified twenty-three significant uncertainties within Mixed-Mode (MM) operating environments. Using a multi-product, multi-level dependent demand MRP simulation model within an MM operating environment driven by planned order release, an experimental programme has been carried out that showed finished products delivered late to be insensitive as a performance measure. Parts Delivered Late (PDL) was found to be more sensitive and has been adopted as the preferred measure. ANOVA on the simulation results validated the cause-and-effect relationships, showing that the higher the level of uncertainty, the worse was delivery performance. Individual uncertainties produced effects that were not discretely recognised in the literature. `Knock-on' effects are created by uncertainties delaying the issue of batches and affected particular Bill of Materials chains. `Compound' effects are caused by uncertainties affecting resource availability and also induced consequent knock-on effects. Simulation results also showed that late deliveries from suppliers, machine breakdowns, unexpected or urgent changes to schedules affecting machines and customer design changes are the most significant uncertainties within the parameter levels modelled. Several significant two-way and three-way interactions were found. The business model of uncertainty represents a practical and pragmatic attempt to act as a diagnostic tool to identify significant underlying causes affecting PDL for MM companies using MR1, enabling more effective application of suitable BAD approaches. Using the business model to drive a continuous improvement programme that monitored both levels of uncertainty and PDL would allow internal and external benchmarking for the efficacy of BAD approaches and for the reduction of uncertainties