Today's supply chains have to cope with volatile markets and extremely high customer demands in a highly competitive global market, in which prices can be compared online within seconds. Therefore, companies are looking for methods to speed up processes and make their logistics operations as efficient as possible. They can accomplish this by applying lean thinking in nearly all business operations: Lean Production, Lean Management, Lean Supply Chain and others. The most recent is Lean Warehousing, which tries to adopt lean techniques from the lean toolbox like 5S, KANBAN, MUDA, KAIZEN and Jidoka. There is some academic literature about Lean Warehousing, which explains these methods and describes how to implement them. The interaction between Lean Warehousing and Warehouse Management Systems (WMS) as not yet been studied.Lean Warehousing (LW) is often understood as a toolbox rather than a strategic alignment and a philosophy. Therefore, the implementation of LW has systemic flaws due to the lack of philosophy understanding, transformational leadership, and change management. To better understand sustainable Lean Warehousing transformation, it is necessary to synthesise knowledge of these theories. This study aims to examine why most of the attempts to implement LW fail and why the current theories of LW do not suffice. It includes a quantitative survery as well as a qualitative survey with managers in the field. The results of the literature review, the surveys and a thorough examination of soft skills as well as elicited innovative factors are all used to form an extensive analysis of successful LW implementation. The development of a comprehensive LW model is necessary.
Dissertationsschrift
Dr. Simon Kallinger studied European Business Administration with a focus on SCM and graduated with the academic degree Dipl.Kfm. (FH) in 2008. During his studies, the author gained extensive practical experience in spare parts logistics at MAN. Fascinated by the control and optimization of internal logistics with logistics software, the author spent the following years in various positions as a consultant, project manager and sales manager for WMS, further expanding his expert knowledge of internal material flow and logistics management. He still works in the field today. The author has also completed a master's degree in industrial engineering in logistics (2011). His interest in lean management and the link to logistics finally led to the academic degree PhD with a dissertation on lean warehousing. In addition, Dr. Kallinger teaches SCM and logistics as a lecturer at a private university.
Textprobe:Kapitel 4.3 Mega Trends in Logistics and Warehousing:For a holistic picture of the logistics sector, it is also necessary to know the current trends as they may have influence on LWI either as a show-stopper or as driver.The study from Keller, S. (2020) describes artificial intelligence and automation as a viatal contribution for many innovation logistics. 34% of the companies surveyed, said that robots and automation were very important. Whereas 38% considered Augmented Reality AR and wearables to be less relevant. The following sub-chapters give an overview about the most important megatrends. (Keller, 2020; Zagurskiy, 2020).4.3.2Big Data:The business drivers of logistics and big data are gaining in quality and quantity (BVL 2014). The main drivers are cost pressure, rising customer demands, lack of skilled workers, process standardisation, but also digitalisation and automation of works order. Therefore, enterprises are looking at big data as it bears a great opportunity to gain deeper insight into operations and processes. With around $900 billions of waste in global manufacturing supply chains (N.N., IDC Manufacturing- Zebra, 2016), there is a vast untapped potential to create new values, to gather and assimilate unprecedented levels of manufacturing data. (N.N., Zebra White Paper, 2014). Having these data makes it far easier to increase efficiency where material handling and labor costs are concerned, but also to a network of connected devices across the entire system. According to Otto (Otto, 2014), Big Data has the potential to transform logistic systems. Logistic Management will be data-driven instead of model-driven with ad-hoc agility instead of planned flexibility. Logistic processes will be probabilistic instead of deterministic. The flow of information will be "streams" instead of "records," and also the flow of material will be self-managed instead of central-managed. Further, the people will decide instead of executing and will be more generalists than specialists.Big Data is closely related to missing WMS modules because these data could be used for predictive analysis. With empirical values from the past, it is possible to forecast future decisions, and therefore it is also possible to realise process optimisation. E.g., the storage location of current stock will be checked and optimised to decrease picking time. Also, stock demand and resource planning can be optimised by big data. (N.N (b), 2016) The current development can be described by some up-to-date topics like Big Data, Digitalisation, or Smart Supply Chain, but one term clarifies this development than transformation as the whole sector is in a flow. A central pillar for this is data or even more qualitative data. Through an entire capturing and meaningful usage of these data, complex processes could be done more efficiently and give transparency at the same time. (Bär, 2016) Büyüközkan and Göcer (2018) go much further in stating that in "... today's emerging market model data centers replace physical warehouses" (Büyüközkan and Göcer, 2018, p.157) and that "...bits replace the physical boxes and bandwidth replaces the physical trucks." (Büyüközkan and Göcer, 2018, p.157).4.3.3Climate change - Green Logistics"Sustainability is emerging as the main consideration throughout the industrial world due to the environmental pollution and degradation happening in a major scale as a result of industrial wastes while lean management is becoming a popular management tool in minimizing waste." (Edirisuriya, Weerabahu and Wickramarachchi 2018, p. 1). This statement clearly describes a relation between lean management and green logistics. Therefore, transport and logistics sector is coming into focus on the green agenda due to the high impact of environmental pollution during their operations. (Lambrechts et al., 2019). More and more organizations try to develop their own social, environmental, and economic indicators in order to measure, impr