Generation of a Data Model for Quotation Costing of Make to Order Manufacturers from Case Studies

For contract or make to order manufacturers, quotation costing is a complex process that is mainly performed based on experience. Due to the high diversity of the product range of these mostly small or medium-sized companies (SMEs) and the poor data situation at the time of quotation preparation, the quality of the calculation is subject to strong variations and uncertainties. The gap between the initial quotation costing and the actual costs to be spent (pre- and post-calculation) is crucial to the existence of SMEs. Digitalization in general can help companies to get a better understanding of processes and to generate data. For improving these processes, an understanding of the important data for that specific process is crucial. Accurate quotation costing for customized products is time-consuming and resource-intensive, as there is a lack of an overview of data to be used within the process. This paper therefore derives a data model for supporting quotation costing in the company, based on literature-based costing procedures and recorded case studies for quotation and calculation. Based on the results, SMEs will have a first overview of the needed data for quotation costing to optimize their calculation process

Tool manufacturing by metal casting in sand moulds produced by additive manufacturing processes

Thesis (D. Tech. ( Mechanical Engineering )) - Central University of technology, Free State, 2012In this study an alternative indirect Rapid Tooling process is proposed. It essentially consists of producing sand moulds by Additive Manufacturing (AM) processes followed by casting of tools in the moulds. Various features of this tool making method have been investigated. A process chain for the proposed tool manufacturing method was conceptually developed. This process chain referred to as Rapid Casting for Tooling (RCT) is made up of five steps including Computer Aided Design (CAD) modeling, casting simulation, AM of moulds, metal casting and finishing operations. A validation stage is also provided to determine the suitability of the tool geometry and material for RCT. The theoretical assessment of the RCT process chain indicated that it has potential benefits such as short manufacturing time, low manufacturing cost and good quality of tools in terms of surface finish and dimensional accuracy. Focusing on the step of AM of the sand moulds, the selection of available AM processes between the Laser Sintering (LS) using an EOSINT S 700 machine and Three Dimensional Printing using a Z-Corporation Spectrum 550 printer was addressed by means of the Analytic Hierarchy Process (AHP). The criteria considered at this stage were manufacturing time, manufacturing cost, surface finish and dimensional accuracy. LS was found to be the most suitable for RCT compared to Three Dimensional Printing. The overall preferences for these two alternatives were respectively calculated at 73% and 27%. LS was then used as the default AM process of sand moulds in the present research work. A practical implementation of RCT to the manufacturing of foundry tooling used a case study provided by a local foundry. It consisted of the production of a sand casting pattern in cast iron for a high pressure moulding machine. The investigation confirmed the feasibility of RCT for producing foundry tools. In addition it demonstrated the crucial role of casting simulation in the prevention of casting defects and the prediction of tool properties. The challenges of RCT were found to be exogenous mainly related to workmanship. An assessment of RCT manufacturing time and cost was conducted using the case study above mentioned as well as an additional one dealing with the manufacturing of an aluminium die for the production of lost wax patterns. Durations and prices of RCT steps were carefully recorded and aggregated. The results indicated that the AM of moulds was the rate determining and cost driving step of RCT if procurement of technology was considered to be a sunk cost. Overall RCT was found to be faster but more expensive than machining and investment casting. Modern surface analyses and scanning techniques were used to assess the quality of RCT tools in terms of surface finish and dimensional accuracy. The best surface finish obtained for the cast dies had Ra and Rz respectively equal to 3.23 μm and 11.38 μm. In terms of dimensional accuracy, 82% of cast die points coincided with die Computer Aided Design (CAD) data which is within the typical tolerances of sand cast products. The investigation also showed that mould coating contributed slightly to the improvement of the cast tool surface finish. Finally this study also found that the additive manufacturing of the sand mould was the chief factor responsible for the loss of dimensional accuracy. Because of the above, it was concluded that light machining will always be required to improve the surface finish and the dimensional accuracy of cast tools. Durability was the last characteristic of RCT tools to be assessed. This property was empirically inferred from the mechanical properties and metallographic analysis of castings. Merit of durability figures of 0.048 to 0.152 were obtained for the cast tools. It was found that tools obtained from Direct Croning (DC) moulds have merit of durability figures three times higher than the tools produced from Z-Cast moulds thus a better resistance to abrasion wear of the former tools compared to the latter

Estimation of Time for Manufacturing of Injection Moulds Using Artifi cial Neural Networks-based Model

Jedna od najvažnijih aktivnosti u izvedbi projektno orijentiranih poslovnih procesa ocjena je potrebnih tehnoloških vremena i troškova. To je rana faza procjene koju provode visoko kvalifi cirani interni stručnjaci. Jedna od najvećih zapreka u toj fazi je precizno defi niranje odnosa između karakteristika proizvoda i potrebnih tehnoloških vremena za izradu kalupa. Ovaj rad predlaže pristup rješavanju tog problema korištenjem umjetnih neuronskih mreža. Razvijeni model pokazuje da je moguće postići prihvatljivu točnost procjene korištenjem lako dostupnih ulaznih podataka.One of the most crucial activities for a successful business is project time and cost estimation. This is an early estimation process which is usually handled by highly skilled, in-house experts. One of the main obstacles in this process is to accurately defi ne the relationship between product properties and the machining hours necessary to manufacture the mould. This article suggests how to address this problem by using artifi cial neural networks (ANN). The developed model shows that it is possible to achieve admissible accuracy of the estimation by using easily obtainable input data

Process assessment for the extended enterprise during early product development using novel computational techniques

Manufacturing practices have evolved over the last quarter of a century in the light of changes to manufacturing technology and demand. To sustain this growth companies are increasingly focused on better design and quicker time to market, to stay one step ahead of the competition. Expanding technology capabilities have included microcomputers and telecommunications. In particular the Internet has allowed businesses to trade with an extended customer base, resulting in a greater demand and perpetuating the cycle. To mirror this statement, businesses are looking increasingly far and wide for suitable suppliers. This work identifies a need in the market for an Internet based supplier selection function, during early product development. The development of this work differs significantly from other process selection methods by the use of the Internet to link companies. It has advantages for product development relating to the scope of the opportunities, diversity of possible manufacturing operations and rapid assessment of processes. In particular the system can be broken down into two main functions. Process Selection (PS) and Factory Selection (FS). The PS method presented enables many processes to be modelled, in multiple organisations for a single product. The Internet is used to gain access to supplier facilities by adopting the same principles as on-line banking, or shopping, for data input and access. The results of these assessments are retained by the system for later analysis. The FS method utilises this data to model and compare supplier attributes, allowing the user to manipulate the data to fit their requirements. Testing of the system has proved encouraging for many operations, including Injection Moulding and CNC Machining. It can be concluded that the identification of manufacturing operations outside the remit of companies' normal scope will create further opportunities for supplier integration

Intelligent conceptual mould layout design system (ICMLDS) : innovation report

Family Mould Cavity Runner Layout Design (FMCRLD) is the most demanding and critical task in the early Conceptual Mould Layout Design (CMLD) phase. Traditional experience-dependent manual FCMRLD workflow results in long design lead time, non-optimum designs and costs of errors. However, no previous research, existing commercial software packages or patented technologies can support FMCRLD automation and optimisation. The nature of FMCRLD is non-repetitive and generative. The complexity of FMCRLD optimisation involves solving a complex two-level combinatorial layout design optimisation problem. This research first developed the Intelligent Conceptual Mould Layout Design System (ICMLDS) prototype based on the innovative nature-inspired evolutionary FCMRLD approach for FMCRLD automation and optimisation using Genetic Algorithm (GA) and Shape Grammar (SG). The ICMLDS prototype has been proven to be a powerful intelligent design tool as well as an interactive design-training tool that can encourage and accelerate mould designers’ design alternative exploration, exploitation and optimisation for better design in less time. This previously unavailable capability enables the supporting company not only to innovate the existing traditional mould making business but also to explore new business opportunities in the high-value low-volume market (such as telecommunication, consumer electronic and medical devices) of high precision injection moulding parts. On the other hand, the innovation of this research also provides a deeper insight into the art of evolutionary design and expands research opportunities in the evolutionary design approach into a wide variety of new application areas including hot runner layout design, ejector layout design, cooling layout design and architectural space layout design

Rapid tooling for carbon fibre compression moulding

Thesis (M. Tech.) -- Central University of Technology, Free State, 2010The aim of this study is to produce more cost effective carbon fibre (CF) parts. To achieve this there must be a saving on materials, labour and time. Thus, a production process to produce cost effective CF moulds while saving time and money is required. This procedure must be suited for the incorporation in the small to medium production ranges. The composite industry is one of the fastest growing industries in the world. Therefore, the faster a mould can be produced, the faster the end product will reach the market. This research project investigates the possibility to sinter CF moulds on the Electro Optical Systems (EOS) Laser Sintering (LS) machine cheaper and faster than the conventional method using computer numerically controlled (CNC) machining. The surface finish produced on the LS machine is not of the same quality as a CNC machined mould, but there are ways to enhance the surface quality of a LS part to the point that it is compatible to the surface quality of a CNC machined mould. The CF moulding process uses many different types of moulding processes. However, it is not possible to use LS parts for all of the available processes to produce CF parts. In this study only one CF moulding process will be investigated, namely compression moulding. The moulds will be designed to be manufactured as cheaply and as quickly as possible. Different methods of mould adapting have been studied to find the cheapest most suitable method of mould design for the LS process

The gilded Buddha - The traditional art of the Newar metal casters in Nepal

This book celebrates in words and images the traditional metal crafts practised for over a thousand years by the creators of religious Buddhist statues in Nepal. The skills of these artisans are nurtured with deep respect for tradition, regarding religion, iconography and technology. Wax modellers, mould makers, casters, fire-gilders and chasers are among the specialists of the Newar ethnic group, whose work is characterised to this day by a melding of age-old technology, great skill, religious observance and contemplation. There are numerous books and exhibition catalogues dedicated to Buddhist art and iconography but little was available about the craft of the artists who turn the religious imagery into metal casts. This book fills this gap, with a thoroughly documented and historical account of the development of this “archaic” technology. The well-informed text and comprehensive photographic coverage constitute the only up-to-date account and full documentation of an art that is 1300 years old but dying out: the “ritual” production of Buddhist statues in the lost wax casting technique. The author, Dr. Alex Furger, is an archaeologist who has studied ancient metallurgy and metalworking techniques over the past four decades. He spent twenty-five years at the head of the Roman site of Augusta Raurica and lives in Basel (Switzerland). He is the author of over 130 articles in scientific journals and twelve books in the field of culture history. The fieldwork for this book led him repeatedly to Nepal, where he met and interviewed dozens of craftsmen in their workshops. This book is addressed to readers interested in culture history, travellers to Asia, collectors of statues of Buddha, (avocational) metalworkers, historians of technology, Buddhists, ethnologists, archaeologists, art historians, scholars of Asia and to libraries and museums

Development of an additive manufacturing decision support system (AMDSS)

PhD ThesisAdditive manufacturing (AM) technology describes a set of processes capable of producing 3D physical products from CAD data directly. The rapid development of AM technologies and their wide applications makes the selection of the suitable process chains and materials a difficult task. Some researchers have tackled this problem by developing selectors that should assist users in their selections. The existing selector systems have some drawbacks: (і) often being outdated even before they were completely developed because new processes and materials are evolving continuously, (іі) representing only the point of view of their developers because users were not involved in the development process and (iii) not being holistic and able to help in all AM aspects for example process chains, materials, finishing methods and machines. This work has developed an updatable decision support system that assists users in their selections regarding AM process chains, materials, finishing methods, and machines. First, the study started by analyzing the available additive manufacturing selector systems and identifying their shortcomings. Secondly, the researcher identified target specifications for the new system, investigated different possible architectures for the system, selected knowledge based system (KBS) and database (DB) architecture to work together as a versatile tool that achieves the required target specifications. Next, the first version of the system was developed. Furthermore, verification and validation processes were made to test the developed system. Three case studies were used for the validation purpose: a typical consumer razor blade and two automotive components. These case studies were manufactured using AM technologies and then a comparison between real life decisions and the developed decision support system decisions were made. In addition, a number of interviews were performed in order to obtain users’ feedback about the first developed version. As a result of the feedback and evaluation a second version of the system was developed and evaluated. The results obtained from the second evaluation suggest that the second version is more effective than the first version during the selection process. To conclude, this study has shown that using KBS and DB together is effective to develop an updatable additive manufacturing decision support system. In addition, the user involvement in the development stage of the system enhances the system performance.The Arab Academy for Science & Technology & Maritime Transport