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Considerable effort is needed to design the software and the material‐flow system to meet the needs of manufacturing which is driven by customer demand. Top management initiative and support is required throughout. Here, Prof. Dr. Sankaran describes the concept developed by Siemens in two major projects.

A common pipeline of apparel design and simulation is adjusting 2D apparel patterns, putting them onto a virtual human model and performing 3D physically based simulation. However, manually adjusting 2D apparel patterns and performing simulations require repetitive adjustments and trials in order to achieve satisfactory results. To support future made-to-fit apparel design and manufacturing, efficient tools for fast custom design purposes are desired. The purpose of this paper is to propose a method to automatically adjust 2D apparel patterns and rapidly generate acustom apparel style for a given human model.

The authors first pre-define a set of constraints using feature points, feature lines and ease allowance for existing apparels and human models. The authors formulate the apparel fitting to a human model, as a process of optimization using these predefined constraints. Then, the authors iteratively solve the problem by minimizing the total fitting metric.

The authors observed that through reusing existing apparel styles, the process of designing apparels can be greatly simplified. The authors used a new fitting function to measure the geometric fitting of corresponding feature points/lines between apparels and a human model. Then, the optimized 2D patterns are automatically obtained by minimizing the matching function. The authors’ experiments show that the authors’ approach can increase the reusability of existing apparel styles and improve apparel design efficiency.

There are some limitations. First, in order to achieve interactive performance, the authors’ current 3D simulation does not detect collision within or between adjacent apparel surfaces. Second, the authors’ did not consider multiple layer apparels. It is non-trivial to define ease allowance between multiple layers.

The authors use a set of constraints such as ease allowance, feature points, feature lines, etc. for existing apparels and human models. The authors define a few new fitting functions using these pre-specified constraints. During physics-driven simulation, the authors iteratively minimize these fitting functions.

ASEA Distribution in Vasteras, Sweden, uses a robotised line for the assembly of small contactors.

In 2003, ITC responded to the high level of obsolete inventory by shifting risk from finished products to manufacturing and raw materials. This required that their supply chain be much more flexible and responsive than it was in the past. By 2006, changes in the supply chain that included moving manufacturing in-house improved flexibility and responsiveness. Obsolete inventory was significantly reduced and the company was much better at matching supply and demand. Cost, however, continued to be higher than that at third parties. The company had to decide on the appropriate tradeoff between cost and responsiveness when structuring its supply chain.

The case illustrates how Wills has changed its supply chain to become more flexible and responsive. This change, however, has come at a cost. The case requires the students to analyze the tradeoff between cost and responsiveness/flexibility to decide on an appropriate level of flexibility/responsiveness. The case also requires the student to understand the relative value of increased flexibility versus increased responsiveness.

The purpose of this paper is to examine the effects of product modularity on four aspects of competitive performance: cost, quality, flexibility, and cycle time.

Constructs were created from a comprehensive survey of the automotive sector. Regression is used to ascertain the relationship between the constructs of product modularity and performance with three different integration strategies as mediators.

Modularity positively and directly influences each aspect of competitive performance for each integration strategy tested. Indirect effects were found for each integration strategy for cost and flexibility; and for manufacturing integration and cycle time.

A product modularity strategy enables simultaneous improvements on multiple dimensions of competitive performance.

This research is the first to empirically validate the effects of product modularity on competitive performance. Furthermore, it provides insight into the exact nature of product modularity's influence on competitive performance.

Purpose: This chapter aims to enlighten the stakeholders on the role and contribution and the issues and challenges of large-scale industries in the wake of the globally unified economies.

Need for the study: Large-scale industries are one of the pillars of any nation and can exercise an immense impact on the numerous facets of the economy of any country. Their role and contribution can benefit all the stakeholders, especially in today’s integrated and interdependent world economies. Hence, there is an absolute need to highlight the issues and challenges and suggest measures to overcome them to promote a resilient global economy.

Methodology: The study gathered data from secondary sources like textbooks, articles, and the internet.

Findings: The findings of the study state that large-scale industries are enormous contributors to employment creation, development of the economy, growth of revenue, research and development (R&D) and innovation, export promotion, and infrastructure. The significant challenges include regulatory compliance, workforce management, economic volatility, political instability, supply chain management, environmental compliance, and technology and infrastructure.

Protectionism, deregulation, public–private partnership, privatisation, and environmental regulation are significant government decisions that affect large-scale industries. The study identifies tax incentives, easy access to financing, and domestic and international trade policies to safeguard large-scale industries’ interests.

Practical implications: Large-scale industries contribute towards the growth of global economic resilience in terms of employment generation, technological advancements, and innovation, fostering international trade in today’s interconnected world.

The purpose of this study is to examine important operational issues related to strategic success factors that are necessary when implementing SCM plans in an organization.

A questionnaire was distributed to top and middle management within a large manufacturing firm, specializing in producing consumer and building products, to examine the importance and the extent to which the selected manufacturing company practiced the strategies based on these identified operational issues.

Reducing cost of operations, improving inventory, lead times and customer satisfaction, increasing flexibility and cross‐functional communication, and remaining competitive appear to be the most important objectives to implement SCM strategies. The responses by the survey respondents indicate that not enough resources were allocated to implement and support SCM initiatives in their divisions. In addition, they perceived that resource allocation could be improved in the areas of better information systems, greater commitment, setting clear‐cut goals, increased training, more personnel, and aligning SCM initiatives with current priorities and resource commitments.

The results will help to provide greater understanding of strategic and operational issues that support SCM framework and implementing SCM strategies to reduce supply chain‐wide costs and meeting customer service levels.

The results will be useful for business managers to understand and implement SCM plans in terms of their importance and the company's culture.

This paper aims to report on findings of a cross‐sector empirical study of the sources and drivers of supply chain vulnerability.

The research was undertaken in accordance with the realist tradition. It begins with a descriptive exploratory stage involving an in‐depth exploratory case study of aerospace industry supply chains, validated through in‐depth interviews with managers representing other “critical sectors” of the UK economy. This is followed by an explanatory theoretical stage. The work is supported throughout with reference to relevant literature sources.

The findings highlight the absence of any widespread understanding of the scope of and dynamic nature of the problem, which should be considered from multiple perspectives and at four levels of analysis: value stream/product or process; asset and infrastructure dependencies; organisations and inter‐organisational networks; and social and natural environment.

The paper is normative rather than positive, so focuses on understanding why supply chains are vulnerable to disruption, rather than presenting itself as a prescription for management. The paper does not investigate academic definitions or existing taxonomies of risk.

The work provides some useful insights for practising managers and policy makers.

The paper reports on empirical research, then draws as appropriate on network theory and complex systems perspectives to produce a conceptual model of a supply chain as in interactive adaptive system.