Lean and green – a systematic review of the state of the art literature

The move towards greener operations and products has forced companies to seek alternatives to balance efficiency gains and environmental friendliness in their operations and products. The exploration of the sequential or simultaneous deployment of lean and green initiatives is the results of this balancing action. However, the lean-green topic is relatively new, and it lacks of a clear and structured research definition. Thus, this paper’s main contribution is the offering of a systematic review of the existing literature on lean and green, aimed at providing guidance on the topic, uncovering gaps and inconsistencies in the literature, and finding new paths for research. The paper identifies and structures, through a concept map, six main research streams that comprise both conceptual and empirical research conducted within the context of various organisational functions and industrial sectors. Important issues for future research are then suggested in the form of research questions. The paper’s aim is to also contribute by stimulating scholars to further study this area in depth, which will lead to a better understanding of the compatibility and impact on organisational performance of lean and green initiatives. It also holds important implications for industrialists, who can develop a deeper and richer knowledge on lean and green to help them formulate more effective strategies for their deployment

An Integrated Framework to Assess ‘Leanness’ Performance in Distribution Centres

The theory behind lean philosophy is to create more value with less. Effective lean management enables organisations to exceed customer expectations while reducing costs. Despite the fact that numerous practices and approaches are used in the process of implementing lean philosophy and reducing waste within supply chain systems, little effort has been directed into assessing the leanness level of distribution and its impact on overall performance. Given the vital role of distribution units within supply chains, this research aims to develop a comprehensive lean assessment framework that integrates a selected set of statistical, analytical, and mathematical techniques in order to assess the ‘leanness’ level in the distribution business. Due to the limited number of published articles in the area of lean distribution, there are no clear definitions of the underlying factors and practices. Therefore, the primary phase of the proposed framework addresses the identification of lean distribution dimensional structure and practices. The other two phases of the framework discuss the development of a structured model for lean distribution and address the process to find a quantitative lean index for benchmarking lean implementation in distribution centres. Integrating the three phases provides the decision makers with an indicator of performance, subject to applying various lean practices. Incorporating the findings of a survey that sent to 700 distribution businesses in Ireland along with value stream mapping, modelling, simulation, and data envelopment analysis, has given the framework strength in the assessment of leanness. Research outcomes show that lean distribution consists of five key dimensions; workforce management, item replenishment, customers, transportation, and process quality. Lean practices associated with these dimensions are mainly focused on enhancing the communication channels with customers, simplifying the distribution networks structure, people participating in problem solving and a continuous improvement process, and increasing the reliability and efficiency of the distribution operations. The final output of the framework is two key leanness indices; one is set to measure the tactical leanness level, while the second index represents the leanness at the operational level. Both indices can effectively be used in evaluating the lean implementation process and conducting a benchmarking process based on the leanness level

Towards Leaner Healthcare Facility: Application of Simulation Modelling and Value Stream Mapping

Recently, the application of lean thinking in healthcare has grown significantly in response to rising demand caused by population growth, ageing and high expectations of service quality. However, insufficient justifications and lack of quantifiable evidence are the main obstacles to convince healthcare executives to adopt lean. Therefore, this paper presents a methodology that integrates lean tools with simulation to enhance the quality of patient care in healthcare facilities. This enables healthcare organisations to dedicate more time and effort to patient care without extra cost to the organisation or to the patient. Value stream mapping is used to identify value-added and non-value-added activities.. Then, a comprehensive simulation model is developed to account for the variability and complexity of healthcare processes and to assess the gains of proposed improvement strategies. An extensive analysis of results is provided and presented to managers to illustrate the potential benefits of adapting lean practices

Proposition of a method for stochastic analysis of value streams

This article aims at proposing a method to stochastically analyze values streams taking into consideration the effect of critical uncertainty sources on lead time. The proposed method combines value stream mapping (VSM) and Monte Carlo simulation to identify improvement opportunities. To illustrate this approach, we carried out a case study in the special nutrition value stream of a Brazilian public hospital. Results show that the proposed method allows the identification of improvement opportunities that would not be considered in the classical deterministic VSM approach. Further, the integration of the stochastic analysis enables the determination of a more realistic lead time, which supports a more assertive planning and scheduling of the value stream. The proposed method addresses a fundamental gap in traditional VSM without adding much complexity to the analysis procedure, which is a common practical issue in previous works that integrated other stochastic methods into VSM

Improving productivity of road surfacing operations using value stream mapping and discrete event simulation

The Highways Infrastructure is one of the most valuable asset owned by the public sector. Efficient operations of Highways have the success of national and local economies as well as the quality of life of the general public, dependent on it. Ensuring smooth traffic operations requires maintenance and improvements of the highest standard. This research investigates integration of Discrete Event Simulation (DES) and Value Stream mapping (VSM) to enhance the productivity of the delivery of road surfacing operations by achieving higher production rates and minimum road closure times. Research approach involved use of primary data, collected from direct observation, interviews, review of archival records and productivity databases. Based on this, process maps and value stream maps were developed, which were subsequently used to produce discrete event simulation models, for exploration of different optimisation scenarios

Digital twin and Value Stream Mapping of Warehousing in Era of Industry 4.0

The rapid pace of technological development and high competition make the business employ proper approaches to assess the effectiveness of their value creation process or supply chains. The dynamic business environment enhances the uncertainty and the risk of not meeting the business goals. Warehouses might be able to address some levels of uncertainty such as demand fluctuations. Yet, inventory accumulation may lead to becoming a source of inefficiency from the lean methodology perspective. Therefore, the application of the lean methodology and its well-known method, Value Stream Mapping (VSM), has not received much attention in the warehouse efficiency assessment context. On the other hand, Industry 4.0 refers to the ongoing fourth industrial revolution promoting connectivity and information sharing with some key enabling technologies, including the internet of things (IoT), simulation, and digital twin. The digital twin technology is considered a strategic technology and offers a practical way for a system performance assessment. This paper aimed to introduce an approach that integrates the VSM method with the digital twin. The proposed structured approach can be used for the performance evaluation of a warehouse while adapting to the dynamic nature of warehousing. The developed digital model can be used for real-time warehouse performance monitoring and control when connected with the physical warehouse through communication devices. The proposed approach in this paper is applied to a real case to demonstrate its applicability

A simulation-enhanced lean design process

A traditional lean transformation process does not validate the future state before implementation, relying instead on a series of iterations to modify the system until performance is satisfactory. An enhanced lean process that includes future state validation before implementation is presented. Simulation modeling and experimentation is proposed as the primary validation tool. Simulation modeling and experimentation extends value stream mapping to include time, the behavior of individual entities, structural variability, random variability, and component interaction effects. Experiments to analyze the model and draw conclusions about whether the lean transformation effectively addresses the current state gap can be conducted. Industrial applications of the enhanced lean process show it effectivenessPeer Reviewe

Enhanced Value Stream Mapping for Improving Turnaround Process Efficiency in Oil and Gas Industry

Turnaround maintenance (TAM) is one of the most important maintenance strategies to minimise the risk of production losses. Managing these TAM projects is challenging as for its complexity due to the involvement of massive man powers and financial resources. The aim of this research is to develop an enhanced-Value Stream Mapping (enhanced-VSM) framework to effectively improve TAM efficiency. Four theoretical enhancements are made to the conventional VSM method and validation results show the successful implementation