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The purpose of this paper is to identify effective factors, their impact, and find estimation models of the most well-known productivity measurement, hours-per-vehicle (HPV), in the automotive industry in North American manufacturing plants.

Data used in this study were from North American plants that participated in the Harbour’s survey from 2002 to 2006. Data are synthesized using a uniform methodology from information supplied by the plants and supplemented with plant visits by Harbour Consulting auditors. Overall, there are 355 manufacturing plants in the statistical sample from ten different automakers’ brands including DCX, Ford, GM, Honda, Cami, Nummi, Auto Alliance, Mitsubishi, Nissan, and Toyota. The multiple linear regression was used to analyze the data and derive the HPV regression equations.

HPV is a widely recognized production performance indicator that is used by a significant percentage of worldwide automakers. During the study period, the HPV was reduced 54.75 minutes on average in each year. Annual production volume, platform sharing (PS), and flexible manufacturing (FM) factors improve HPV. However, vehicle variety, salaried employees’ percentage of the workforce, available annual working days, and launching a new model penalize HPV. Launching a new model and adding a new variety in body styles or chassis configurations raise the HPV about 2.189 and 0.642 hours, respectively, depending on the car class; however, manufacturing plants compensate for this issue by using PS and FM strategies.

The plants which stopped production of a specific product also are included in this study and were treated similar to the regular plants. The medium duty segment was excluded from the data set due to the fact that the number of observations available was too low. The study can be repeated with additional new factors such as the level of plants’ automation and lean manufacturing either for North American or European companies.

The research investigates current strategies that help automakers to enhance their production performance and reduce their productivity gap. HPV regression equations that are provided in this research may be used effectively to help car makers to set guidelines to improve their productivity with respect to internal and external constraints, strength, weakness, opportunities, and threats.

The purpose of this paper is to analyze lean strategic practices being implemented in manufacturing facilities throughout Pennsylvania and West Virginia and identify the difficulty in implementing those lean practices.

A skip logic questionnaire was developed into multiple sections for analysis; demographics of respondents, identification of the knowledge and practice of lean methods, interpretation of lean application, strategic direction of lean methods, measurements of expertise, and difficulties for practicing lean. The questionnaire was sent to 327 manufacturing facilities where 51 usable responses were collected for the study.

Lean manufacturing is a widely recognized and practiced business philosophy as a significant percentage of manufacturers have implemented some variation of practice. However, the extent of knowledge does not mirror awareness. The application of lean manufacturing practices is not readily appropriate for every company, but adopting the concept of customer-focussed waste reduction to maximize value can be universally applied as waste reduction was the most prominent practice pursued. Lean practitioners found that poka-yoke and installing new process equipment have the highest degree of benefits from implementation while 5S and eliminating waste were the least difficult practices to implement. In general, the management personnel of the companies have an influential effect on lean manufacturing pursuance. This is illustrated by the fact of high agreement between facilities that resistance to change from employees is the most prominent difficulty for implementation followed by limited technical knowledge of lean manufacturing at operational and conceptual levels.

The research findings are from a subset of manufacturing companies in Pennsylvania and West Virginia and may not represent all of the companies on a national level. The results must be interpreted in the context of the data acquisition approach due to the extent of the sample size involved, the procedure for how data were collected, and assuming that each lean strategic practice has the same weight to calculate the facility lean index.

The results provide insight about the effect of facility size and years of lean practicing for various lean strategic practices. The most beneficial and least difficult lean strategies, their implementation level, and the real challenges for implementing lean were also identified to help both lean practitioner and non-practitioner for the lean journey.

The research investigates current lean strategic practices pursued by manufacturers throughout Pennsylvania and West Virginia and identifies obstacles to implementation of lean practices. Lean manufacturing is widely sought after as a continuous improvement program, but success is divided. This study characterizes lean manufacturing comprehension while identifying knowledge areas of strengths and deficiencies. There lacks an established structure for lean practices to pursue. Therefore, this study provides manufacturers a measure for comparing their position for refined decision making.

To identify the factors that need to be addressed by Indian industry to steeply ramp up its production and productivity in the coming years, so as to achieve the goal of the country becoming a 5 trillion dollar economy by 2025.

Lean Management Leaders in Indian Industry (LMLII), i.e. those companies in India who are well known for having adopted TQM, BE and Lean methods for many years, and achieved success in their business) in Indian industry were selected and surveys were done between 2013 and 2017, to assess the status of LM adoption, by using the LESAT (version 2.0) survey tool. A longitudinal empirical study has been done, over a period of five years, so that the identification of factors is based on a few years’ data rather than a one year, spot-check or snapshot view. A new method, titled the ‘Three Step Reverse Exploratory Factor Analysis Procedure (TSREP)’, has been attempted to identify the ‘root causes’.

LMLII's have improved in their adoption of LM over these years by about 10%. The root causes that can help in further advancement in adoption have been identified and classified under six component factors.

The identification of LMLII's has been done based on the experience and views of experts in TQM/ BE/ Lean in India. Since this is a first of such study (viz., the term LMLII is being defined and used for the first time), this methodology has been adopted. However, in future, a systematic way to assess the criteria for LMLII's could be designed. Secondly, the sample size of LMLII's needs to be fully representative of the industry.

By using the results of this study, Indian companies can accelerate their LM adoption programmes, leading to quantum jumps in production and productivity, so as to achieve the 5 trillion USD economy by 2025. The practical implications are immense.

Since LM is a bundle of Lean, TQM and BE, companies adopting LM will, due to the inclusion of waste reduction through 5S, JIT, kaizens and continuous improvement, address the Triple Bottom Line (TBL) protocol of the UN. TBL has comprehensive implications on society and environment, climate change and sustainability of business.

This work is original, at least in three ways. First, in the use of the concept of ‘LML’. Second, there is no previous longitudinal study done on Indian industry in LM. Third, the TSREP is being used for the first time. The value of this research is in its findings, in the identification of key factors for future growth and the use of a novel technique for improving upon the accuracy, analytical rigour and legitimacy of the results.

The purpose of this paper is to identify the factors that promote the successful adoption of lean practices in manufacturing firms operating in developing economies in South America.

Based on the results obtained from using structural equation modeling to analyze the collected data, the authors argue that manufacturing organizations need to identify the factors that assist in successfully adopting lean practices in manufacturing firms operating in developing economies in South America. A dataset of 1,809 responses, gathered from manufacturing firms as part of the World Management Survey, was used to find support for the proposed hypotheses.

Several hypotheses were tested finding that lean practice success factors such as organizational targets proved to have a significant and positive relationship with the mediating factor, performance management. Likewise, performance management was also found to have a significant and positive relationship with lean practices adoption. Human capital management (HCM) has a significant but negative predictive relationship with lean practices.

The empirical results of this study provide valuable managerial insights. The results are therefore limited to the economies analyzed and to the variables surveyed as part of the World Manufacturing Survey research.

The results of this research provide a starting point for researchers to continue studying the key lean practice factors and relationships in the achievement of improved performance management, thereby helping managers in developing strategies to improve the lean capabilities of their practices. This, in turn, will increase the organization's competitive advantage sustainably.

This paper identifies and tests the impact of key factors on successful lean practices adoption in South American organizations in the manufacturing sector.

A growing body of evidence points to the influence of location and allocation decisions on the structure of healthcare networks. The authors introduced a three-level hierarchical facility location model to minimize travel time in the healthcare system under uncertainty.

Most healthcare networks are hierarchical and, as a result, the linkage between their levels makes it difficult to specify the location of the facilities. In this article, the authors present a hybrid approach according to data envelopment analysis and robust programming to design a healthcare network. In the first phase, the efficiency of each potential location is calculated based on the non-radial range-adjusted measure considering desirable and undesirable outputs based on a number of criteria such as the target area's population, proximity to earthquake faults, quality of urban life, urban decrepitude, etc. The locations deemed suitable are then used as candidate locations in the mathematical model. In the second phase, based on the proposed robust optimization model, called light robustness, the location and allocation decisions are adopted.

The developed model is evaluated using an actual-world case study in District 1 of Tehran, Iran and relevant results and different sensitivity analyses were presented as well. When the percentage of referral parameters changes, the value of the robust model's objective function increases.

The contributions of this article are listed as follows: Considering desirable and undesirable criteria to selecting candidate locations, providing a robust programming model for building a service network and applying the developed model to an actual-world case study.

This paper aims to investigation of processes for Pb²⁺ elimination from water/wastewater as a significant public health issue in many parts of world. The removal of Pb²⁺ ions by various nanocomposites has been explained from water/wastewaters. ZnO-based nanocomposites, as eco-friendly nanoparticles with unique physicochemical properties, have received increased attention to remove Pb²⁺ ions from water/wastewaters.

In this review, different ZnO-based nanocomposites were reviewed for their application in the removal of Pb²⁺ ions from the aqueous solution, typically for wastewater treatment using methodology, such as adsorption. This review focused on the ZnO-based nanocomposites for removing Pb²⁺ ions from water and wastewaters systems.

The ZnO-based nanocomposite was prepared by different methods, such as electrospinning, hydrothermal/alkali hydrothermal, direct precipitation and polymerization. Depending on the preparation method, various types of ZnO-based nanocomposites like ZnO-metal (Cu/ZnO, ZnO/ZnS, ZnO/Fe), ZnO-nonmetal (PVA/ZnO, Talc/ZnO) and ZnO-metal/nonmetal (ZnO/Na-Y zeolite) were obtained with different morphologies. The effects of operational parameters and adsorption mechanisms were discussed in the review.

The findings may be greatly useful in the application of the ZnO-based nanocomposite in the fields of organic and inorganic pollutants adsorption.

The present study is novel, because it investigated the morphological and structural properties of the synthesized ZnO-based nanocomposite using different methods and studied the capability of green-synthesized ZnO-based nanocomposite to remove Pb²⁺ ions as water contaminants.

The current review can be used for the development of environmental pollution control measures.

This paper reviews the rapidly developing field of nanocomposite technology.