Special Session on Industry 4.0

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Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments

Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment

Business Case and Technology Analysis for 5G Low Latency Applications

A large number of new consumer and industrial applications are likely to change the classic operator's business models and provide a wide range of new markets to enter. This article analyses the most relevant 5G use cases that require ultra-low latency, from both technical and business perspectives. Low latency services pose challenging requirements to the network, and to fulfill them operators need to invest in costly changes in their network. In this sense, it is not clear whether such investments are going to be amortized with these new business models. In light of this, specific applications and requirements are described and the potential market benefits for operators are analysed. Conclusions show that operators have clear opportunities to add value and position themselves strongly with the increasing number of services to be provided by 5G.Comment: 18 pages, 5 figure

A comparison of processing techniques for producing prototype injection moulding inserts.

This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed

Lean technology development

Thesis (S.M.)--Massachusetts Institute of Technology, Technology and Policy Program, 2001.Includes bibliographical references (leaves 89-91).In today's corporate world, successful technology management is separating market leaders from laggards. Because technology is in constant change and what is state-of-the-art today will be obsolete tomorrow, it is not companies with the best technologies that ultimately succeed. Instead, successful companies are those that succeed in institutionalizing and sustaining an efficient technology development process. Moreover, this process must be continuously improved by applying new techniques and concepts to cope with the increasing challenges of technology management. This thesis will explore the extent to which Lean principles can be applied in technology development and how they can contribute to achieving new technology development imperatives (fast cycle time, increasing number of technology introductions, etc.). In order to answer these questions, the thesis proceeds in a logical manner by decomposing the objectives of technology development into organizational solutions using Axiomatic Design. Then, Lean principles as they have developed within the Product Development Focus Team of the Lean Aerospace Initiative are mapped into the above decomposition. The research concludes that under some additional considerations, Lean principles do lead to the achievement of technology development objectives. More, the above theoretical research is applied to a real world case: Technology development at Ford Motor Company. After an assessment of the current process, opportunities of improvement are identified and a leaner process is proposed. Finally, issues and opportunities with OEMs-Suppliers partnerships for new technological systems development are studied. The objective was to formulate policies and make recommendations for a better management of technology supply.by Salim Bouzekouk.S.M

QFD as a tool to improve negotiation process, product quality, and market success, in an automotive industry battery components supplier

30th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2021) 15-18 June 2021, Athens, GreeceThe automotive industry faces major megatrends such as climate change and emissions control, digital transformation, and increased customer power, resulting in more intensive competition, and higher sophisticated vehicles. The application of QFD (Quality Function Deployment) can be particularly valuable to link customer expectations with the technical characteristics of the product. In the case of products, such as batteries for electric vehicles, where technology is not yet mature, and the technical requirements (e.g., autonomy) are continuously more demanding, this is particularly relevant. The QFD customer-oriented product development technique is applied to a cover of a battery pack, to improve the negotiation process with the car manufacturer, the automotive industry battery components supplier company and its suppliers, to ensure market success once the product is released. The application of the HoQ revealed that Product Design and Tolerancing are the main technical requirements with the most impact over the battery cover development, followed the Leakage ratio. This research confirms that the voice of the customer could be quite generic, and it is critical that these requirements are translated into engineering requirements, which, in turn, can be translated into items that can be measured quantitatively and actionable within the company. The application of the affinity diagram was found to be quite valuable to address the significant amount of subjective information, and it is also relevant that OEMs have a desire to standardize the electric vehicle platforms at least on fewer and general sizes, hinting the need for more collaborative team approaches.info:eu-repo/semantics/publishedVersio

Simulation Study for Multi-Echelon Multi-Depot Supply Chain System Using Live Data

The manufacturing industry is eager to implement the advancements of the fourth industrial revolution (Industry 4.0) due to the magnitude of the benefits it can provide. Hence, Industry 4.0 opens a wide avenue for researchers to explore possibilities in the field of the supply chain. This project focuses on building a decision framework for a supply chain system with disruptions. The impact of strategic decisions under the condition of unprecedented events for a vehicle routing problem (VRP) using simulation models is studied here. Those results help the supply chain managers in making sound decisions regarding different scenarios of disruption in VRP. To achieve this, multiple cases under different scenarios of facility disruption are considered. For all cases, the dependent parameter, namely, retailer service level and lost revenue, form the basis of the decision framework. The concept of live data is implemented by making retailer demand, current inventory at the depot, the position of the vehicle in the network and the current number of units in transit as the input data