Understanding the linkages between lean practices and performance improvements in Indian process industries

Purpose The purpose of this paper is to investigate the impact of lean practices on performance improvement of process industries in India. Design/methodology/approach Based on a survey of Indian process industries, this paper proposes two sets of hypothesis to examine if there is any statistically significant impact of lean practices on certain specific performance metrics. First, the sample is classified into two classes of process industries: the adopters of lean and those who have not yet adopted the lean practices in their manufacturing operations. Then statistical tests are conducted to measure the differences in the level of performance between the two classes of Indian process industries with respect to nine performance measures. The survey results are augmented by two in-depth case studies. Case studies include one from lean adopter firms (a refinery) and another from the firms that have not yet adopted the lean practices (a primary metal manufacturing unit). Findings A survey result of 121 Indian process industries shows that adoption of lean practices results in a positive impact on inventory control, waste elimination, cost reduction, productivity, and quality improvement in process industries. On the other hand, based on the sample data on Indian process industries, no statistically significant improvement could be found on the lot size or space utilization between lean adopters and their counterparts. Practical implications This research provides guidance to the managers on how adoption of lean practices results in better performance in process industries in several operational areas. Originality/value To the knowledge, this study is the first attempt to analyze the impact of lean practices on a set of specific performance metrics in Indian process industry. Although this study focuses on the Indian process industry, the authors believe that findings of the research can inform other practitioners and researchers who are considering implementing lean in process industry sector in other developing countries like India. </jats:sec

Stretched or noded orbital densities and self-interaction correction in density functional theory

Semilocal approximations to the density functional for the exchange-correlation energy of a many-electron system necessarily fail for lobed one-electron densities, including not only the familiar stretched densities but also the less familiar but closely related noded ones. The Perdew-Zunger (PZ) self-interaction correction (SIC) to a semilocal approximation makes that approximation exact for all one-electron ground- or excited-state densities and accurate for stretched bonds. When the minimization of the PZ total energy is made over real localized orbitals, the orbital densities can be noded, leading to energy errors in many-electron systems. Minimization over complex localized orbitals yields nodeless orbital densities, which reduce but typically do not eliminate the SIC errors of atomization energies. Other errors of PZ SIC remain, attributable to the loss of the exact constraints and appropriate norms that the semilocal approximations satisfy, suggesting the need for a generalized SIC. These conclusions are supported by calculations for one-electron densities and for many-electron molecules. While PZ SIC raises and improves the energy barriers of standard generalized gradient approximations (GGAs) and meta-GGAs, it reduces and often worsens the atomization energies of molecules. Thus, PZ SIC raises the energy more as the nodality of the valence localized orbitals increases from atoms to molecules to transition states. PZ SIC is applied here, in particular, to the strongly constrained and appropriately normed (SCAN) meta-GGA, for which the correlation part is already self-interaction-free. This property makes SCAN a natural first candidate for a generalized SIC. Published under license by AIP Publishing.Peer reviewe

Product Modularization Considering Cost and Manufacturability of Modules

It is argued that modular architecture allows us to create large product variety at lower cost, and in a shorter development cycle time. While it has been widely recognized that modular design improves assemblability, the manufacturability of modules themselves have rarely been considered during modularization. This paper presents a formal and integrated framework for product modularization by optimizing manufacturability of modules and costs of modularization during the earlier stages of product development. A fuzzy logic approach is used to handle the vague and imprecise product information available during the concept development phase of product development. The framework also facilitates sensitivity analysis to provide design engineers and managers with deeper insights on tradeoffs among conflicting design objectives. The methodology is validated through a case study on the modularization of an automotive climate control system

An integrated fuzzy-goal-programming-based framework for selecting suppliers in strategic alliance formation

There has been an exponential growth in the number of strategic alliances formed in the last decade between manufacturers and their suppliers. Yet 60-70% of these alliances fail in their first year. One of the reasons for such failure is the incompatibility of members of the alliance. Hence, there is a need for a tool to help decision makers to rate the compatibility of potential partners in a strategic alliance. This paper fulfills this requirement by presenting an integrated method for rating the compatibility of potential members of a strategic alliance. The method utilizes a model based on fuzzy logic/goal programming to analyze the vague, imprecise, and usually subjective information regarding the compatibility of potential suppliers that is available during the early formation of a strategic partnership. A sample case study is presented to demonstrate the application of the framework.

A set-covering model for optimizing selection of portfolio of microcontrollers in an automotive supplier company

The sourcing decisions of microcontrollers in automotive industries are complex to manage largely due to the increasing complexity of products requirements, multiple suppliers, and the nature of microcontroller pricing structures. This paper presents a set-covering model that allows the user to select the most economical microcontrollers that meet all the critical product requirements while minimizing the total cost. The optimization process is carried out in two phases. The first phase deals with the construction of a buildable combination matrix by mapping out the critical product requirements against the microcontroller specifications. In the second phase, the model makes an optimal assignment of microcontrollers to each feasible or buildable product by utilizing economies of scales offered by large microcontroller volumes. Lot size constraints are used to handle the step function in the microcontrollers pricing structure. A case study from Visteon Corporation is used to demonstrate the application of the model. Pilot implementation of the model shows a potential saving of nearly two millions over a 4-year planning horizon.Large scale optimization Strategy planning Case study Set-covering model