One of the important design elements for a good production system is material handling. In cases where it is not well-designed, it can be the bottleneck in the system. Moreover, it can cause a lot of wastes such as waiting time, idle time, and excessive transportation and cost. In this study, material handling in lean-based production environments is taken into account. Depending on the lean structure of the production systems such as being pull-based, smooth, and repetitive, delivering the materials to the stations periodically becomes important. At this point, milk-run trains are highly used in real applications since they enable the handling of required amount of materials on a planned basis. With this study, it is aimed to develop a specific model for milk-run trains which travel periodically in the production environment on a predefined route in equal cycle times with the aim of minimizing work-in-process and transportation costs. Since the milk-run trains having equal cycle times start their tours at the same time intervals, it becomes simple to manage them. For this reason, they are used in lean production systems where level scheduling is performed. The developed model is based on mixed-integer linear programming, and since it is difficult to find the optimum solution due to the combinatorial structure of the problem, a novel heuristic approach is developed. A numerical example is provided so as to show the applicability of the mathematical model and the heuristic approach.
For Industry 4.0 to be effective, interdisciplinary knowledge from engineering, computer science, business, and various other academic disciplines is crucial . Lean Management stands out as a consolidated managerial paradigm that tries to tackle the previously mentioned challenges, with a large history since it was grounded in the 1940s by Toyota production managers [9,10,11,12]. The main goal of both Industry 4.0 and lean management is to find ways to deal with an ever increasing complexity in the manufacturing industry that nowadays partially stems from digitisation, as well as mass customisation. Although Industry 4.0 puts the focus on the technological elements, lean methods seek to find ways to reduce the complexity by designing clear and controllable processes that minimise non value-adding activities throughout the value chain . To achieve this goal, a wide range of tools, initially conceived under the umbrella of the Toyota just-in-time (JIT) system, such as synchronised production, Kanban, single minute exchange of die (SMED), cross-functional work force , and others, that evolved to gain its own field of development as total productive maintenance (TPM) or total quality management (TQM) , have been developed and put into practice in manufacturing environments. These techniques have shown significant positive effects in different industries and even synergistic benefits through their combined implementation [16,17]. Combining the methodologies from Industry 4.0 and lean manufacturing has been an increasingly popular research topic, resulting in the so-called Lean 4.0 . There are mixed opinions regarding whether lean management is needed to enable Industry 4.0 or Industry 4.0 advance lean management . Yet, one of the key ideas about Industry 4.0 is the integration of varied technologies due to the limited effect of focusing on a single technology . In fact, several of the many lean tools have been examined in the context of Industry 4.0 [21,22,23], leading to the conclusion that a leaner production is easier to integrate into an Industry 4.0 context and, in many cases, it is possible to combine the ideas and techniques from both frameworks [24,25,26,27,28]. Moreover, it seems to be a necessary evolutionary step for further raising the level of operational excellence (i.e., to coordinate actions, to optimise resource efficiency, to improve work safety, to decrease in cost) . In this sense, one successful Lean 4.0 approach is the integration of JIDOKA(自働化) into the Industry 4.0 framework, which has shown great potential [29,30,31] and motivates this work.
A scoping review was conducted to gain a deeper understanding of how LM impacts frontline healthcare professionals. Findings of the review are reported in accordance with the PRISMA-SCR guideline . This choice of methodology is justified by the emerging nature of the evidence on the impact of LM on the health workforce . The aim of this review is to provide a comprehensive overview of the existing literature and put forward a research agenda for future research on this topic. With that aim in mind, a review strategy was developed and approved by all members of the research team prior to systematically searching the following academic databases in February 2020: Scopus, Emerald, EBSCO business premier and PubMed. The search strategy was not published or registered in an open platform. The choice of databases allowed for the identification of relevant publications in the fields of health science, as well as management studies where LM originated. Papers were searched by combining a set of topic-related keywords (Lean approach, Lean process, Lean method, Lean transformation, Lean philosophy, Lean principles, Lean practices, Lean process improvement, Lean management, Lean healthcare, Lean thinking, Lean production, Lean six sigma, Toyota production system) and a group of setting-related keywords (health care, healthcare, hospital). Only peer-reviewed articles were searched; news articles, conference proceedings, magazines, trade publications and book chapters were excluded using the exclusion parameters of the online databases during the search phase. No starting date was specified, and articles published up to 29 February 2020 were included. Table 2 portrays the use of the search strategy using Scopus database as an example. Additional file 1 includes an example of the search string used to query PubMed and Scopus.
Furthermore, despite examining the use of multiple LM tools and techniques, only one of the studies considered Lean holistically, as an organisational, system-wide approach designed to target waste and improve the production of value . The majority of the studies, instead, focused on assessing the outcomes of using specific Lean-related tools or techniques. Accordingly, a large number of the studies adopted an evaluation design that, while useful, substantially limits the generalisability of the results and the conclusions that can be drawn about the impact of LM on staff. Generalisability was also hindered by the adoption of single case study designs, often conducted in one country, as well as by the absence of theoretical framing of the study or results, or both. 2b1af7f3a8