Smart, Innovative and Intelligent Technologies Used in Drug Designing

Smart and intelligent computational methods are essential nowadays for designing, manufacturing and optimizing new drugs. New and innovative computational tools and algorithms are consistently developed and applied for the development of novel therapeutic compounds in many research projects. Rapid developments in the architecture of computers have also provided complex calculations to be performed in a smart, intelligent and timely manner for desired quality outputs. Research groups worldwide are developing drug discovery platforms and innovative tools following smart manufacturing ideas using highly advanced biophysical, statistical and mathematical methods for accelerated discovery and analysis of smaller molecules. This chapter discusses novel innovative applications in drug discovery involving use of structure-based drug design which utilizes geometrical knowledge of the three-dimensional protein structures. It discusses statistical and physics based methods such as quantum mechanics and classical molecular dynamics which can also play a major role in improving the performance and in prediction of computational drug discovery. Lastly, the authors provide insights on recent developments in cloud computing with significant increase in smart and intelligent computational power thus allowing larger data sets to be analyzed simultaneously on multi processor cloud systems. Future directions for the research are outlined.

Software Development Tools to Automate CAD/CAM Systems

In today’s modern manufacturing, software automation is crucial element for leveraging novel methodologies and integrate various engineering software environments such Computer aided design (CAD), Computer aided process planning (CAPP), or Computer aided manufacturing (CAM) with programming modules with a common and a comprehensive interface; thus creating solutions to cope with repetitive tasks or allow argument passing for data exchange. This chapter discusses several approaches concerning engineering software automation and customization by employing programming methods. The main focus is given to design, process planning and manufacturing since these phases are of paramount importance when it comes to product lifecycle management. For this reason, case studies concerning software automation and problem definition for the aforementioned platforms are presented mentioning the benefits of programming when guided by successful computational thinking and problem mapping.

Hybrid Evolutionary Optimization Algorithms

The novel industrial manufacturing sector inevitably faces problems of uncertainty in various aspects such as raw material availability, human resource availability, processing capability and constraints and limitations imposed by the marketing department. These problems have to be solved by a methodology which takes care of such unexpected information. As the analyst faces this man made chaotic and due to natural disaster problems, the decision maker and the implementer have to work collaboratively with the analyst for taking up a decision on an innovative strategy for implementation. Such complex problems of vagueness and uncertainty can be handled by the hybrid evolutionary intelligence algorithms. In this chapter, a new hybrid evolutionary optimization based methodology using a specific non-linear membership function, named as modified S-curve membership function, is proposed. The modified S-curve membership function is first formulated and its flexibility in taking up vagueness in parameters is established by an analytical approach. This membership function is applied for its useful performance through industrial production problems by employing hybrid evolutionary optimization algorithms. The novelty and the originality of this non-linear S-curve membership function are further established using a real life industrial production planning of an industrial manufacturing sector. The unit produces 8 products using 8 raw materials, mixed in various proportions by 9 different processes under 29 constraints. This complex problem has a cubic non-linear objective function. Comprehensive solutions to a non-linear real world objective function are achieved thus establishing the usefulness of the realistic membership function for decision making in industrial production planning.

Meta-Heuristic Structure for Multiobjective Optimization Case Study

In engineering optimization, one often encounters scenarios that are multiobjective (MO) where each of the objectives covers different aspects of the problem. It is hence critical for the engineer to have multiple solution choices before selecting of the best solution. In this chapter, an approach that merges meta-heuristic algorithms with the weighted sum method is introduced. Analysis on the solution set produced by these algorithms is carried out using performance metrics. By these procedures, a novel chaos-based metaheuristic algorithm, the Chaotic Particle Swarm (Ch-PSO) is developed. This method is then used generate highly diverse and optimal solutions to the green sand mould system which is a real-world problem. Some comparative analyses are then carried out with the algorithms developed and employed in this work. Analysis on the performance as well as the quality of the solutions produced by the algorithms is presented in this chapter.

Fair Share of Supply Chain Responsibility for Low Carbon Manufacturing

Large amounts of carbon emissions and pollution are generated during the manufacturing process for consumer goods. Low carbon manufacturing has been increasingly enquired or requested by stakeholders. However, international trade blurs the responsibility for carbon emissions reduction and raises the questions of responsibility allocation among producers and consumers. Scholars have been examining the nexus of producer versus consumer responsibility among supply chains. Recently, there have been discussions on the share of producer and consumer responsibility. Both producer and consumer responsibility approaches have intrinsic shortcomings and are ineffective in curbing the rise of carbon emissions in supply chains. Shared responsibility based on the equity principle attempts to address these issues. This chapter relates a case study of carbon impact on China’s export and economy with scenarios which show that the benefits of carbon reduction by producers can trickle down along the supply chain and motivate the sharing responsibility under certain circumstances. The share of producer and consumer responsibility for low carbon manufacturing can be enabled when embodied carbon emissions in goods and services are priced and such accurate information is available. A mechanism engaging the global participation is recommended. The author calls for further research on the system pricing embodied carbon emission, the universal standard to calculate the embodied carbon emissions and to disclose the information, and the way to secure global cooperation and participation.

The Role of Brand Loyalty on CRM Performance

This chapter introduces the framework and causal model of customer value, customer satisfaction, brand loyalty, and customer relationship management performance in terms of the innovative manufacturing and marketing solutions. It argues that dimensions of customer value, customer satisfaction, and brand loyalty have mediated positive effect on customer relationship management performance. Furthermore, brand loyalty positively mediates the relationships between customer value and customer relationship management performance and between customer satisfaction and customer relationship management performance. Customer value is positively correlated with customer satisfaction. Understanding the theoretical learning is beneficial for organizations aiming to increase customer relationship management performance and achieve business goals.

A Framework for the Modelling and Optimisation of a Lean Assembly System Design with Multiple Objectives

The newest assembly system is lean assembly, which is specifically designed to respond quickly and economically to the fluctuating nature of the market demands. Successful designs for these systems must be capable of satisfying the strategic objectives of a management in manufacturing company. An example of such systems is the so-called walking worker assembly line WWAL, in which each cross-trained worker travels along the line to carry out all tasks required to complete a job. Design approaches for this system have not been investigated in depth both of significant role in manual assembly process design; productivity and ergonomics. Therefore these approaches have had a limited success in actual applications. This chapter presents an innovative and integrated framework which offers significant potential improvement for productivity and ergonomics requirements in WWAL design. It establishes a systematic approach clearly demonstrating the implementation of a developed framework based on the simultaneous application of mathematical and meta- heuristic techniques.

Antecedents of Green Manufacturing Practices

The purpose of this chapter is to identify green supply chain practices and study their impact on firm performance. In this study, the authors have adopted a two-pronged strategy. First, they reviewed extant literature published in academic journals and reports published by reputed agencies. They identified key variables through literature review and developed an instrument to measure the impact of GSCM practices on firm performance. The authors pretested this instrument using five experts drawn from industry having expertise in GSCM implementation and two academicians who have published their articles in reputed journals in the field of GSCM and sustainable manufacturing practice. After finalizing the instrument, the study then randomly targeted 175 companies from CII Institute of Manufacturing database and obtained response from 54 which represent 30.85% response rate. The authors also performed non-response bias test to ensure that non-response bias is not a major issue. They further performed PLSR analysis to test our hypotheses. The results of the study are very encouraging and provide further motivation to explore other constructs which are important for successful implementation of GSCM practices.

Towards Smart Manufacturing Techniques Using Incremental Sheet Forming

The current world’s economical crisis raised the necessity from the industry to produce components cheaper and faster. In this sense, the importance of smart manufacturing techniques, proper articulation between CAD/CAM techniques and integrated design and assessment becomes critical. The Single Point Incremental Forming (SPIF) process represents a breakpoint with traditional forming processes, and possibly a new era in the small batches production or customized parts, being already used by automotive industry for light components. While classical stamping processes need a punch, a die, a holder and a press, in the SPIF process the final geometry is achieved incrementally through the action of a punch with a spherical head. Since the blank is clamped at the edges, there is no need to employ a die with the shape of the final part. However, this process must be further improved in terms of speed and dimensional accuracy. Because the process is cheap and easy to implement, it is currently the subject of intensive experimental and numerical research, but yet not deeply understood. This chapter gives an overview on the techniques currently being employed to optimize the process feasibility.

Design of Anti-Metallic RFID for Applications in Smart Manufacturing

Anti-metallic passive RFID tags play a key role in manufacturing automation systems adopting RFID techniques, such as manufacturing tool management, logistics and process control. A novel long range passive anti-metallic RFID tag fabrication method is proposed in this chapter, in which a multi-strip High Impendence Surface (HIS) with a feeding loop is designed as the antenna radiator. Firstly, the bandwidth enhancement methods for passive RFID tags based on micro strips are discussed. Then, a RFID tag design based on multi-strip antenna is proposed and its radiation efficiency is analyzed. After that, some key parameters of the RFID antenna proposed are optimized from the viewpoint of radiation efficiency and impedance match performance. Targeted for manufacturing plants with heavy metallic interfering, the proposed RFID tag can significantly enhance the radiation efficiency to improve the reading range as well as the bandwidth. Finally, some RFID tag prototypes are fabricated and tested to verify their performance and applicability against metallic environment, and the experimental results show that these fabricated RFID tags have outstanding reading performance and can be widely used in manufacturing plant full of heave metallic interfering.