Logistics network planning

The Cambridge Engineering Selector (CES) is a tool that focuses on material, process, and shape combinations of product design. The Resource Consumption Model (RCM) is a tool that focuses on production process resources, resource costs, production volume, production capacity, and manufacturing cycle time. Both tools help identify viable manufacturing process alternatives to meet stated manufacturing objectives.

Today supply chain management has become one of the crucial factors for gaining and sustaining a competitive advantage. Enterprises that can more effectively manage their supply chain network have a higher likelihood of success in the marketplace. To this end, companies need not only make the “make” or “buy” decisions but also differentiate across potential suppliers in order to improve operational performance, and hence, supplier selection is one of the key decisions aiding effective supply chain management. Many studies have also pointed out that the integration of product and supply chain is a key factor for profitability and efficiency. However, prior studies mostly address supply chain performance after the creation of a new product; and only a few studies discuss when and how to incorporate supply chain decisions during product design. In the studies that cover product design, product family and product platform concepts are presented as enabling vehicles for mass customization, which require a considerable investment, and hence might be out of reach for small to medium size enterprises (SME). Accordingly, there is a need to develop a methodology that can consider manufacturability and supply chain issues at the product design stage. This paper presents a graph theory based optimization methodology to tackle this problem. The supplier selection issue is considered by evaluating its impact on both engineering (e.g., process planning) and operational performance (e.g., cost and time), which are then aggregated as the supply chain performance at the conceptual design stage. A case study in the bicycle industry demonstrates the advantages of this methodology. The synchronized structure of the supply chain and the product design results in simultaneous optimization of both design and supply chain decisions during the early design stages.

In recent years, the competitive pressure on manufacturing companies shifted them from mass production to mass customization to produce large variety of products. It is a great challenge for companies nowadays to produce customized mixed flow mode of production to meet customized demand on time. Due to large variety of products, the storage system to deliver variety of products to production lines influences on the timely production of variety of products, as investigated from by simulation study of an inefficient storage system of a real Company, in the current research. Therefore, current research proposed a slotting optimization model with mixed model sequence to assemble in consideration of the final flow lines to optimize whole automated storage and retrieval system (AS/RS) and distribution system in the case company. Current research is aimed to minimize vertical height of centre of gravity of AS/RS and total time spent for taking the materials out from the AS/RS simultaneously. Genetic algorithm is adopted to solve the proposed problem and computational result shows significant improvement in stability and efficiency of AS/RS as compared to the existing method used in the case company.

The discipline of materials engineering and science spans the scope of the physical and chemical makeup of materials, the strength and other mechanical properties that are critical to appropriate decisions in product design, the relationships between and among materials, and finally, the analysis of actual or potential failures.In the forensic aspect, the primary question in materials engineering and science is why a materials failure occurred. To make this determination, the materials engineer and scientist may ask the fundamental questions: When did the material fail in relation to a sequence of events? Did it fail and cause an event, or did it fail as a result of the event? Was design or manufacturing a factor? Was the choice of material a factor? Was inadequate maintenance a factor?This discussion of materials engineering and science will explain the most important terms and concepts used when describing and investigating materials failures. It will discuss some common failure modes for the four classes of materials: metals, ceramics/glasses, polymers, and composites.Failure analysis procedures, including methods of testing and microscopic examination, will be discussed. A list of useful materials science and engineering references is provided for further background.

Collaborative innovation, in which multiple companies try to incorporate content generated by consumers into new product development, is becoming increasingly popular. The fact that overconfidence usually increases with more data means that companies integrating large amounts of consumer-generated content in collaborative innovation have a strong tendency to be overconfident. We study the effects associated with overconfidence in collaborative innovation, where overconfidence is defined as a decision maker’s cognitive bias that leads to an overestimation of the precision of an uncertain event. In our collaborative innovation model, an online shopping platform collects and assimilates content (such as online reviews) generated by consumers to generate a product design and then sells that design to the manufacturer, after which the manufacturer produces a corresponding new product and sets a retail price. In this article, we mainly focus on how overconfidence impacts the product design strategy, pricing strategies, and decision makers’ equilibrium profit levels. We demonstrate that overconfidence can be a positive force for collaborative innovation and even lead to a win-win-win situation for the platform, manufacturer, and consumer. We show that overconfidence can make the platform change its product design strategy from aesthetic-oriented in the unbiased scenario to functionality-oriented in the biased scenario. Furthermore, we show that each of the two product design strategies has its own scope of application; neither is universally dominant.

Management Insights

Problem of Practice: A question most companies face while outsourcing any IT project is vendor selection — which vendor to select or whether to opt for multiple vendors? Most companies face difficulties while selecting vendors as they do not have adequate information about the vendors' cost structure. New research by Jain and team1 can now help navigate this age-old dilemma as it looks at a key factor beyond the pricing—the 'learning efficiency'. The essay provides insights on how companies can implement these learnings in a practical setting

From the Publisher: Thirty years ago, computers seemed more science fiction than business fact. Today we have e-commerce, e-marketing, computerized scheduling,manufacturing, and a whole new field called information technology. Computers now have applications for every facet of your business. Information Systems and Technology for the Non-Information Systems Executive explores the practical and efficient use of computer technology-both software and hardware-for all types of business applications. In a simple and reader friendly style Shim presents information on data bases, networking, and telecommunications. He explains popular accounting, tax, finance, management, manufacturing, and marketing software-making them easy to understand and use. In addition, he provides real-life examples that illustrate the applications of decision support systems, executive information systems, and artificial intelligence systems such as financial modeling, budgeting, strategic planning and control, forecasting, data analysis, inventory planning, and optimization software. You do not need to know programming to understand your information systems. Written for business managers and entrepreneurs who may not have extensive computer experience, Information Systems and Technology for the Non-Information Systems Executive covers information systems in all phases and functional areas of business to help you make the best decisions. It provides a wealth of current and essential information for managers and executives of all types of organizations. Your success depends on keeping abreast of the latest applications and thinking in information technology. This book gives you the competitive edge.

In recent years, with the rapid development of computer hardware and algorithm technology, artificial intelligence has shown significant advantages in product design, medical diagnosis and finance. This paper applies the method of visual analysis to reveal the research hotspots of user-centred product design in the field of artificial intelligence and discusses the future development trend of this field. The data for this study comes from 670 documents in the Web of Science database. Using visualisation tools such as CiteSpace 6.1.1 and VOSviewer, the literature on "Artificial Intelligence (AI)", "Users" and "Product Design (PD)" was analysed for the period from 2004 to 2024. Product Design (PD)" literature was analysed. Product Design (PD)" literature was analysed. It was found that over the past two decades, research in this field can be broadly categorised into three phases: initial development, rapid development and fluctuating growth. China has become a major force in this research area and has made a significant impact. The main research directions focus on technology and management innovation, advanced technology and industrial change, information technology and applications, and technology and user experience. The results of the study expose that user-centered product and service design needs to pay more attention to intelligence and personalization as a way to drive the development of service quality improvement.

The ability for a product developer to successfully launch useful products is tied to the company’s product design strategies. Due to the complexity of perception and expectations on new product design from customers and the diverse perspectives of the product developer, any approaches without systematically analyzing these complex criteria to assess decision making on product design strategies are therefore deemed as inappropriate. A systematic approach to determine appropriate product design strategies based on the attributes of product design and customer expectations should thus be considered. This research focuses on the investigation of shape formulation process using evolutionary grammars (EG) and non-linear product design analysis with Kano model to refine product design strategies. Through the strategic integration of evolutionary grammars and Kano model, the complex effects on the evolutionary design process and product design strategies are revealed. In order to demonstrate the viability of the approach, experiments are described and a comparison analysis on three EG-Kano reference models is performed. Upon determining the appropriate EG-Kano reference model, the product developer can refine the product design strategies to suit the targeted market.

In the world of business competition, entrepreneurs are demanded to be able to respond and act quickly to face increasingly fierce business competition within the scope of one location. Entrepreneurs are expected to be able to compete healthily and competitively to create the most exciting innovations to maintain their loyalty. Each entrepreneur will make every effort to influence the buyer's decision by consumers so that they are interested in the products they market. This explanatory research uses primary data collected from respondents to be processed through SPSS, data and statistical application. In this study, the objects are the relationship between price, product design, location, store atmosphere, and consumer decisions. The subject of this research is a Culinary Cafe located in Malang City. The sampling technique used is purposive sampling, and the sample obtained is 100 respondents. The data analysis used is descriptive statistics, and multiple regression is used to test the hypothesis in this study. The results show that the variables of price, product design, and location significantly affect purchase decisions, while store atmosphere has no significant effect on purchase decisions. And from the simultaneous test results, the four independent variables together affect purchase decisions at Culinary Cafes in Malang City. Companies can use the implications of this research to make decisions to attract consumers to make purchases.

This study aims to determine the effect of Product Quality, Product Design, Green Product, Brand Image, and Purchase Decision variables. The results of the research on the t test indicate that the Product Quality variable (X1) has no significant effect on purchasing decisions with a significance value of 0.432 > 0.05 and a t count value 1.98498 < t table 4.020; Product Design variable (X2) has no significant effect on purchasing decisions with a significance value of 0.931 > 0.05 and a t-count value of 1.98498 < t table 4.020; Green Product variable (X3) has no significant effect on purchasing decisions with a significance value of 0.270 > 0.05 and a t-count value of 1.98498 < t table 4.020; Brand Image variable (X4) has no significant effect on purchasing decisions with a significance value of 0.451 > 0.05 and a t-count value of 1.98498 < t table 4.020. Based on the results of the F test, the variables of product quality, product design, Green Products and Brand Image simultaneously do not have a positive effect on the purchasing decision variables, because the significance value is 0.681 > 0.05.
 Keywords : Product Quality, Product Design, Green Product, Brand Image, Purchase Decision

The Indian manufacturing industry is growing rapidly, and supply chain management (SCM) plays the most important role in the industry. In SCM, customer satisfaction in terms of quantity, quality and on time delivery is the most important critical factor. To satisfy this requirement, the best third-party logistics (3PL) service provider is required. Therefore, the selection of the best third-party logistics provider is one of the basic requirements in SCM. Logistics services are the backbone of an economy, providing the efficient, cost effective flow of goods and services on which other commercial sectors depend. The logistics companies work as the outsourced or third-party service providers and support the organization's logistics functions. In this study, we identified some important criteria for 3PL implementation in SCM in Indian manufacturing industries. With the help of this study, supply chain managers from small to medium sized manufacturing industries can simplify the selection process for 3PL vendors. This study will help in the selection of the best vendor from such a competitive group and provide justification for the selection.

Machine learning for multiscale modeling in computational molecular design

In today's highly competitive global marketplace, the pressure on organizations to find new ways to create value and deliver it to their customers grows ever stronger. In the last two decades, the logistics function has moved to center stage. There has been a growing recognition that effective logistics management throughout the firm and supply chain can greatly assist in the goal of cost reduction and service enhancement. The keys to success in Logistics Management (LM) require heavy emphasis on integration of activities, cooperation, coordination and information sharing throughout the firm and the entire supply chain, from suppliers to customers. To be able to respond to the challenge of integration, modem businesses need sophisticated decision support systems based on powerful mathematical models and solution techniques, together with advances in information and communication technologies. Both industry and academia alike have become increasingly interested in using LM as a means of responding to the problems and issues posed by changes in the logistics function. This paper presents a brief discussion on the important issues in LM and argues that metaheuristics can play an important role in solving complex logistics problems derived from designing and managing logistics activities within the supply chain as a single entity. Among several possible metaheuristic approaches, we will focus particularly on Iterated Local Search, Tabu Search and Scatter Search as the methods with the greatest potential for solving LM related problems. We also briefly present some successful applications of these methods.