Reliability modelling and verification of manufacturing processes based on process knowledge management

Reliability modelling and verification is indispensable in modern manufacturing, especially for product development risk reduction. Based on the discussion of the deficiencies of traditional reliability modelling methods for process reliability, a novel modelling method is presented herein that draws upon a knowledge network of process scenarios based on the analytic network process (ANP). An integration framework of manufacturing process reliability and product quality is presented together with a product development and reliability verification process. According to the roles of key characteristics (KCs) in manufacturing processes, KCs are organised into four clusters, that is, product KCs, material KCs, operation KCs and equipment KCs, which represent the process knowledge network of manufacturing processes. A mathematical model and algorithm is developed for calculating the reliability requirements of KCs with respect to different manufacturing process scenarios. A case study on valve-sleeve component manufacturing is provided as an application example of the new reliability modelling and verification procedure. This methodology is applied in the valve-sleeve component manufacturing processes to manage and deploy production resources.

Manufacturing challenges with fabrication of large size mechanical harmonic drives

In truck manufacturing, the exhaust and air inlet pipes are specialized equipment that requires highly skilled, heavy machinery and small batch production methods. This paper describes a project to develop the computer numerically controlled (CNC) pipe bending process for a truck component manufacturer. The company supplies a huge range of heavy duty truck parts to the domestic market and is a significant supplier in Australia. The company has been using traditional methods of machine assisted manual pipe bending techniques. In a drive of continuous improvement, the company has acquired a pre-owned CNC bending machine capable of bending pipes automatically up to 25 bends. However, due to process mismatch, this machine is only used for single bending operation. The researchers studied the bending system and changed the manufacturing process. Using an example exhaust pipe as the benchmark, a significant drop of manufacturing lead time from 70 minutes to 40 minutes for each pipe was demonstrated. There was also a decrease of material cost due to the multiple bends part in one piece without cutting excessive materials for each single bend like it used to be.

Achieving quality improvement in the mask manufacturing industry by using Six Sigma technique

The Six Sigma technique is one of the quality management strategies and is utilised for improving the quality and productivity in the manufacturing process. It is inspired by the two major project methodologies of Deming’s "Plan – Do – Check – Act (PDCA)" Cycle which consists of DMAIC and DMADV. Those two methodologies are comprised of five phases. The DMAIC project methodology will be comprehensively used in this research. In brief, DMAIC is utilised for improving the existing manufacturing process and it involves the phases Define, Measure, Analyse, Improve, and Control. Mask industry has become a significant industry in today’s society since the outbreak of some serious diseases such as the Severe Acute Respiratory Syndrome (SARS), bird flu, influenza, swine flu and hay fever. Protecting the respiratory system, then, has become the fundamental requirement for preventing respiratory deceases. Mask is the most appropriate and protective product inasmuch as it is effective in protecting the respiratory tract and resisting the virus infection through air. In order to satisfy various customers’ requirements, thousands of mask products are designed in the market. Moreover, masks are also widely used in industries including medical industries, semi-conductor industries, food industries, traditional manufacturing, and metal industries. Notwithstanding the quality of masks have become the prioritisations since they are used to prevent dangerous diseases and safeguard people, the quality improvement technique are of very high significance in mask industry. The purpose of this research project is firstly to investigate the current quality control practices in a mask industry, then, to explore the feasibility of using Six Sigma technique in that industry, and finally, to implement the Six Sigma technique in the case company to develop and evaluate the product quality process. This research mainly investigates the quality problems of musk industry and effectiveness of six sigma technique in musk industry with the United Excel Enterprise Corporation (UEE) Company as a case company. The DMAIC project methodology in the Six Sigma technique is adopted and developed in this research. This research makes significant contribution to knowledge. The main results contribute to the discovering the root causes of quality problems in a mask industry. Secondly, the company was able to increase not only acceptance rate but quality level by utilising the Six Sigma technique. Hence, utilising the Six Sigma technique could increase the production capacity of the company. Third, the Six Sigma technique is necessary to be extensively modified to improve the quality control in the mask industry. The impact of the Six Sigma technique on the overall performance in the business organisation should be further explored in future research.

Empirical study to identify the key business activities contributing to manufacturing business performance

Purpose: Within the context of high global competitiveness, knowledge management (KM) has proven to be one of the major factors contributing to enhanced business outcomes. Furthermore, knowledge sharing (KS) is one of the most critical of all KM activities. From a manufacturing industry perspective, supply chain management (SCM) and product development process (PDP) activities, require a high proportion of company resources such as budget and manpower. Therefore, manufacturing companies are striving to strengthen SCM, PDP and KS activities in order to accelerate rates of manufacturing process improvement, ultimately resulting in higher levels of business performance (BP). A theoretical framework along with a number of hypotheses are proposed and empirically tested through correlation, factor and path analyses. Design/methodology/approach: A questionnaire survey was administered to a sample of electronic manufacturing companies operating in Taiwan to facilitate testing the proposed relationships. More than 170 respondents from 83 organisations responded to the survey. The study identified top management commitment and employee empowerment, supplier evaluation and selection, and design simplification and modular design as the key business activities that are strongly associated with the business performance. Findings: The empirical study supports that key manufacturing business activities (i.e., SCM, PDP, and KS) are positively associated with BP. The findings also evealed that some specific business activities such as SCMF1,PDPF2, and KSF1 have the strongest influencing power on particular business outcomes (i.e., BPF1 and BPF2) within the context of electronic manufacturing companies operating in Taiwan. Practical implications: The finding regarding the relationship between SCM and BP identified the essential role of supplier evaluation and selection in improving business competitiveness and long term performance. The process of forming knowledge in companies, such as creation, storage/retrieval, and transfer do not necessarily lead to enhanced business performance; only through effectively applying knowledge to the right person at the right time does. Originality/value: Based on this finding it is recommended that companies should involve suppliers in partnerships to continuously improve operations and enhance product design efforts, which would ultimately enhance business performance. Business performance depends more on an employee’s ability to turn knowledge into effective action.

Knowledge sharing for strengthening manufacturing operation and business performance

Manufacturing companies have strived to enhance managerial and technical capabilities to improve business performance. Building these capabilities requires effective share of knowledge - the strategic resource. Specifically, knowledge sharing (KS) between different manufacturing departments can improve manufacturing processes since leveraging organisational knowledge plays an enssential role in achieving competitive advantage. This paper presents an empirical investigation into the impact of KS on the effectiveness of supply chain management (SCM) and the product development process (PDP) in achieving desired business performance (BP). A questionnaire survey was administered from electronic manufacturing companies operating in Taiwan. 168 valid responses were received and used to statistically examine the relationships between the concepts (SCM, PDP, KS, BP). The study findings reveal that within the Taiwanese electronic manufacturing companies KS is an essential enabler for facilitating the effectiveness of SCM and PDP in achieving desired BP.

Numerical optimization of soft-mold aided co-curing process of advanced grid-stiffened composite structures

The co-curing process for advanced grid-stiffened (AGS) composite structure is a promising manufacturing process, which could reduce the manufacturing cost, augment the advantages and improve the performance of AGS composite structure. An improved method named soft-mold aided co-curing process which replaces the expansion molds by a whole rubber mold is adopted in this paper. This co-curing process is capable to co-cure a typical AGS composite structure with the manufacturer’s recommended cure cycle (MRCC). Numerical models are developed to evaluate the variation of temperature and the degree of cure in AGS composite structure during the soft-mold aided co-curing process. The simulation results were validated by experimental results obtained from embedded temperature sensors. Based on the validated modeling framework, the cycle of cure can be optimized by reducing more than half the time of MRCC while obtaining a reliable degree of cure. The shape and size effects of AGS composite structure on the distribution of temperature and degree of cure are also investigated to provide insights for the optimization of soft-mold aided co-curing process.

Process Analytical Technology Approach on Fluid Bed Granulation and Drying : Identifying Critical Relationships and Constructing the Design Space

Fluid bed granulation is a key pharmaceutical process which improves many of the powder properties for tablet compression. Dry mixing, wetting and drying phases are included in the fluid bed granulation process. Granules of high quality can be obtained by understanding and controlling the critical process parameters by timely measurements. Physical process measurements and particle size data of a fluid bed granulator that are analysed in an integrated manner are included in process analytical technologies (PAT). Recent regulatory guidelines strongly encourage the pharmaceutical industry to apply scientific and risk management approaches to the development of a product and its manufacturing process. The aim of this study was to utilise PAT tools to increase the process understanding of fluid bed granulation and drying. Inlet air humidity levels and granulation liquid feed affect powder moisture during fluid bed granulation. Moisture influences on many process, granule and tablet qualities. The approach in this thesis was to identify sources of variation that are mainly related to moisture. The aim was to determine correlations and relationships, and utilise the PAT and design space concepts for the fluid bed granulation and drying. Monitoring the material behaviour in a fluidised bed has traditionally relied on the observational ability and experience of an operator. There has been a lack of good criteria for characterising material behaviour during spraying and drying phases, even though the entire performance of a process and end product quality are dependent on it. The granules were produced in an instrumented bench-scale Glatt WSG5 fluid bed granulator. The effect of inlet air humidity and granulation liquid feed on the temperature measurements at different locations of a fluid bed granulator system were determined. This revealed dynamic changes in the measurements and enabled finding the most optimal sites for process control. The moisture originating from the granulation liquid and inlet air affected the temperature of the mass and pressure difference over granules. Moreover, the effects of inlet air humidity and granulation liquid feed rate on granule size were evaluated and compensatory techniques used to optimize particle size. Various end-point indication techniques of drying were compared. The ∆T method, which is based on thermodynamic principles, eliminated the effects of humidity variations and resulted in the most precise estimation of the drying end-point. The influence of fluidisation behaviour on drying end-point detection was determined. The feasibility of the ∆T method and thus the similarities of end-point moisture contents were found to be dependent on the variation in fluidisation between manufacturing batches. A novel parameter that describes behaviour of material in a fluid bed was developed. Flow rate of the process air and turbine fan speed were used to calculate this parameter and it was compared to the fluidisation behaviour and the particle size results. The design space process trajectories for smooth fluidisation based on the fluidisation parameters were determined. With this design space it is possible to avoid excessive fluidisation and improper fluidisation and bed collapse. Furthermore, various process phenomena and failure modes were observed with the in-line particle size analyser. Both rapid increase and a decrease in granule size could be monitored in a timely manner. The fluidisation parameter and the pressure difference over filters were also discovered to express particle size when the granules had been formed. The various physical parameters evaluated in this thesis give valuable information of fluid bed process performance and increase the process understanding.

Heuristic algorithms for scheduling of a batch processor in automobile gear manufacturing

In this paper we address a scheduling problem for minimising total weighted tardiness. The motivation for the paper comes from the automobile gear manufacturing process. We consider the bottleneck operation of heat treatment stage of gear manufacturing. Real life scenarios like unequal release times, incompatible job families, non-identical job sizes and allowance for job splitting have been considered. A mathematical model taking into account dynamic starting conditions has been developed. Due to the NP-hard nature of the problem, a few heuristic algorithms have been proposed. The performance of the proposed heuristic algorithms is evaluated: (a) in comparison with optimal solution for small size problem instances, and (b) in comparison with `estimated optimal solution' for large size problem instances. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently obtaining near-optimal solutions (that is, statistically estimated one) in very reasonable computational time.

Scheduling identical parallel machines with machine eligibility restrictions to minimize total weighted flowtime in automobile gear manufacturing

In this paper, we address a scheduling problem for minimizing total weighted flowtime, observed in automobile gear manufacturing. Specifically, the bottleneck operation of the pre-heat treatment stage of gear manufacturing process has been dealt with in scheduling. Many real-life scenarios like unequal release times, sequence dependent setup times, and machine eligibility restrictions have been considered. A mathematical model taking into account dynamic starting conditions has been proposed. The problem is derived to be NP-hard. To approach the problem, a few heuristic algorithms have been proposed. Based on planned computational experiments, the performance of the proposed heuristic algorithms is evaluated: (a) in comparison with optimal solution for small-size problem instances and (b) in comparison with the estimated optimal solution for large-size problem instances. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently yielding near-statistically estimated optimal solutions in a reasonable computational time.

Design and process selection for joints in flexible materials

The application of high performance textiles has grown significantly in the last 10 to 15 years. Various research groups throughout the United Kingdom, such as the Department of Trade and Industry, have identified technical textiles as a field for future development. There is little design guidance for joining of flexible materials or general property models that can be applied to theses materials. This lack is due to the large diversity of properties, structures and resulting behaviours of the materials that are classified as "Flexible Materials". This dissertation explores the issues that are involved in characterising the materials at the fibre, bulk and textile levels. Different units of measurement are used for each stage of the manufacturing process of flexible materials and this disparity creates problems when trying to make general comparisons (e.g. comparing textiles to polymer films). Thus, a possible solution to this is to create selection charts that allow designers to compare the strength of materials for a given mass per unit area. A design tool was created using the Cambridge Engineering Selector (CES) software to enable the selection of joining processes for material. The tool is effective in selecting a reduced number of viable joining processes. Through case studies it was shown that designers are required to examine the selected processes (identified by the software) in greater detail - in particular the economics and geometry of the joint - in order to identify the optimum joining process.

An analysis of manufacturing simulation software.

As a management tool Similation Software deserves greater analysis from both an academic and industrial viewpoint. A comparative study of three packages was carried out from a 'first time' use approach. This allowed the ease of use and package features to be assessed using a simple theoretical benchmark manufacturing process. To back the use of these packages an objective survey on simulation use and package features was carried out within the manufacturing industry.This identified the use of simulation software, its' applicability and preception of user requirements thereby proposing an ideal package.

Infant milk formula manufacture: process and compositional interactions in high dry matter wet-mixes

Infant milk formula (IMF) is fortified milk with composition based on the nutrient content in human mother's milk, 0 to 6 months postpartum. Extensive medical and clinical research has led to advances in the nutritional quality of infant formula; however, relatively few studies have focused on interactions between nutrients and the manufacturing process. The objective of this research was to investigate the impact of composition and processing parameters on physical behaviour of high dry matter (DM) IMF systems with a view to designing more sustainable manufacturing processes. The study showed that commercial IMF, with similar compositions, manufactured by different processes, had markedly different physical properties in dehydrated or reconstituted state. Commercial products made with hydrolysed protein were more heat stable compared to products made with intact protein, however, emulsion quality was compromised. Heat-induced denaturation of whey proteins resulted in increased viscosity of wet-mixes, an effect that was dependant on both whey concentration and interactions with lactose and caseins. Expanding on fundamental laboratory studies, a novel high velocity steam injection process was developed whereby high DM (60%) wet-mixes with lower denaturation/viscosity compared to conventional processes could be achieved; powders produced using this process were of similar quality to those manufactured conventionally. Hydrolysed proteins were also shown to be an effective way of reducing viscosity in heat-treated high DM wet-mixes. In particular, using a whey protein concentrate whereby β-Lactoglobulin was selectively hydrolysed, i.e., α-Lactalbumin remained intact, reduced viscosity of wet-mixes during processing while still providing good emulsification. The thesis provides new insights into interactions between nutrients and/or processing which influence physical stability of IMF both in concentrated liquid and powdered form. The outcomes of the work have applications in such areas as; increasing the DM content of spray drier feeds in order to save energy, and, controlling final powder quality.

Multiphysics modeling and its application to the casting process

A modeling strategy is presented to solve the governing equations of fluid flow, temperature (with solidification), and stress in an integrated manner. These equations are discretized using finite volume methods on unstructured grids, which provide the capability to represent complex domains. Both the cell-centered and vertex-based forms of the finite volume discretization procedure are explained, and the overall integrated solution procedure using these techniques with suitable solvers is detailed. Two industrial processes, based on the casting of metals, are used to demonstrate the capabilities of the resultant modeling framework. This manufacturing process requires a high degree of coupling between the governing physical equations to accurately predict potential defects. Comparisons between model predictions and experimental observations are given.

Use of Digital Manufacturing to Improve Management Learning in Aerospace Assembly

The primary goal of this work is to quantify any bene?ts that the use of digital manufacturing methods can offer when used upstream from production, for manufacturing process design, and tool development. Learning at this stage of product development is referred to as management learning. Animated build simulations have been used to develop build procedures and tooling for a panel assembly for the new Bombardier CRJ1000 (Canadair Regional Jet, 100 seat). When the jig format was developed, its simulated performance was compared to that of current CRJ700/900 panel builds to identify and quantify any improvements in terms of tooling cost and panel build time. When comparing like-for-like functions between existing CRJ700/900 (Canadair Regional Jet, 70/90 seat) and the
CRJ1000 tooling, it was predicted that the digitally assisted improvements had brought about a 4.9% reduction in jig cost. An evaluation of the build process for the CRJ1000 uplock panel predicted a 5.2% reduction in the assembly time. In addition to the improvement of existing tooling functions, new jig functionality was added so that both the drilling and riveting functions could be carried out in a single jig for the new RJ1000 panel.

A study of the relationship between process conditions and mechanical strength of mineralized red algae in the preparation of a marine-derived bone void filler

Bone void fillers that can enhance biological function to augment skeletal repair have significant therapeutic potential in bone replacement surgery. This work focuses on the development of a unique microporous (0.5-10 mu m) marine-derived calcium phosphate bioceramic granule. It was prepared fro Corallina officinalis, a mineralized red alga, using a novel manufacturing process. This involved thermal processing, followed by a low pressure-temperature chemical synthesis reaction. The study found that the ability to maintain the unique algal morphology was dependent on the thermal processing conditions. This study investigates the effect of thermal heat treatment on the physiochemical properties of the alga. Thermogravimetric analysis was used to monitor its thermal decomposition. The resultant thermograms indicated the presence of a residual organic phase at temperatures below 500 degrees C and an irreversible solid-state phase transition from mg-rich-calcite to calcium oxide at temperatures over 850 degrees C. Algae and synthetic calcite were evaluated following heat treatment in an air-circulating furance at temperatures ranging from 400 to 800 degrees C. The highest levels of mass loss occurred between 400-500 degrees C and 700-800 degrees C, which were attributed to the organic and carbonate decomposition respectively. The changes in mechanical strength were quantified using a simple mechanical test, which measured the bulk compressive strength of the algae. The mechanical test used may provide a useful evaluation of the compressive properties of similar bone void fillers that are in granular form. The study concluded that soak temperatures in the range of 600 to 700 degrees C provided the optimum physiochemical properties as a precursor to conversion to hydroxyapatite (HA). At these temperatures, a partial phase transition to calcium oxide occurred and the original skeletal morphology of the alga remained intact.