Progress in Lean Manufacturing

This chapter presents the most recent developments with regards the assessment of leanness in manufacturing organizations. Leanness is the measure of the performance of lean manufacturing practices. It is tracked for improvement using assessment frameworks. This chapter reviews prevalent frameworks in order to organize the knowledge, extract the typical and potential uses, establish strengths and weaknesses and reveal ways of improving the extant frameworks. Prevailing frameworks are identified through a search of literature, together with those developed by lean consultants, as well as award-based frameworks. Two main classification schemes are used to organize and compare the frameworks namely the leanness indicators (input data type) used in the frameworks and the applications of the frameworks, representing the inputs and outputs respectively of the frameworks. The key findings of this work can be summarized into: First, most frameworks are generated using either a quantitative or qualitative set of leanness indicators; meanwhile there is a paucity of frameworks that use both types of indicators simultaneously to take advantage of their individual strengths and overcome their respective weaknesses. Second, the frameworks have been used mainly for current-as-is audits, whereas the assessment of proposed improvements is rarely considered. Third, majority of frameworks do not emphasize the interactions between lean practices and the trade- offs between their improvements.

The objective of this chapter is to perform a systematic literature review to identify the main Lean Supply Chain Management (LSCM) practices, barriers to such implementation and contextual factors that influence it. Through this literature examination, it is expected to identify the main gaps related to LSCM implementation and discuss the relevance of research in this topic, indicating future research directions. A systematic literature review (SLR) was devised and adopted, which involved the selection, classification, and evaluation of the literature, resulting in a final portfolio of 60 research articles. It is worth noticing that no temporal delimitation of publications was defined. The content of extant LSCM literature was critically analyzed and synthesized from the perspective of the practices, barriers and contextual factors inherent to LSCM implementation. The analysis of extant literature shows that there is a significant increase in studies related to LSCM, especially after 2011. Based on an extensive systematic review of the literature, we consolidated 18 practices, 12 barriers and 8 contextual factors inherent to LSCM implementation. It is noteworthy that most of the studies published to date on LSCM have focused on outlining practices and their potential benefits, inferring that once companies adopt them the lean implementation would be automatically started. However, such implementation throughout the supply chain is extremely difficult and challenging. From the analysis of this portfolio, it was also verified that most researchers address the three topics (practices, barriers and contextual factors) in an isolated way, not correlating them from a holistic perspective. This research expands previous work on LSCM, strengthening of the body of knowledge on the subject and consolidating the main practices of LSCM, barriers and contextual factors inherent to its implementation. The clear identification of these topics may help researchers and practitioners to anticipate occasional difficulties and set the proper expectations along the LSCM implementation.

This chapter aims to identify, through a systematic literature review, the main Lean Manufacturing (LM) practices, critical success factors (CSF) and barriers within small manufacturing companies’ context. This paper presents a systematic literature review based on the proposed approach denoted as ProKnow-C to identify the correlated bibliographic portfolio (BP). Our findings indicate that the consolidation of specific CSF related to the context of small manufacturing companies reinforces the body of knowledge, reinforcing the establishment of a broader perspective of LM implementation in these companies. Further, the capability of disseminating the continuous improvement mindset across all employees is a significant challenge for these companies, since their leaders are poorly trained in accordance with the underlying LM principles. The recent growth of small companies and their relevance to socioeconomic development has raised the importance of improving their management processes. Particularly for LM implementation, few studies have specifically approached this context whose challenges may be differentiated, highlighting the need for a better comprehension of proper practices, barriers, and CSF.

Healthcare sector had been recently witnessing lean concepts deployment. In order to enable effective implementation of lean concept in the healthcare domain, a structural model needs to be developed. The goal of this study is to analyze the relationship between lean constructs and healthcare performance. The model had been developed with five constructs and 20 measurement variables. The model was developed through the literature on lean deployment in healthcare unit and responses from healthcare experts. Forty-five responses were collected from healthcare experts. Partial least square (PLS) based Structural equation modeling (SEM) approach had been used for analysis. Based on the simulation results, it was found that “management” is the most driving enabler which influences people, process, technology, and other resources of the healthcare unit. The reliability of the developed model has been tested using Cronbach’s alpha and composite reliability. The study presents an attempt to develop a statistical model for lean concepts deployment so as to enhance healthcare performance.

As more companies embrace the concept of Lean Manufacturing (LM), universities should consider changing their curricula since there is a high likelihood that students will participate in some aspects of LM as they begin their professional careers. Thus, it is important to provide appropriate learning experiences to prepare students prior to LM. However, students may learn through several ways and teaching LM has proved to be extremely challenging, especially for engineering students who are not used to abstractions. This paper aims at examining the association between different LM teaching methods and students’ learning preferences to increase their performance in courses. To achieve that, 76 graduate students from Industrial Engineering, who participated in two LM courses with different teaching methods were assessed according to their learning preferences and performance. Each LM course had a specific teaching approach: (i) classroom lectures and exercises (classified as traditional teaching methods), and (ii) problem-based learning (PBL) in real-world problems from companies undergoing an LM implementation. From the eight hypotheses formulated for this study, our results verified four of them, being two for each LM teaching method applied. Further, the effect of the learning dimension “information perception” seems to be more extensive than the others, since students’ performance in both teaching methods is significantly associated with it. The mix between active learning methods and traditional teaching methods may facilitate dialogical learning, encouraging collaboration between students and facilitate the transfer of knowledge on LM.