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Simon Kallinger

Developing of a Lean Warehousing Model. A German Case Study

ISBN: 978-3-95935-604-6

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Produktart: Buch
Verlag: disserta Verlag
Erscheinungsdatum: 12.2022
AuflagenNr.: 1
Seiten: 414
Abb.: 55
Sprache: Englisch
Einband: Paperback


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) has 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.


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). 4.3.2 Big 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 0 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). 4.3.3 Climate 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, improve, and report their sustainability (Farooque and Ahulu, 2017). Also, the study from Edirisuriya, Weerabahu and Wickramarachchi (2018) confirm that companies in the logistics sector contribute considerably due to the wastes and pollution released, but it is also confirmed that implementing lean in parallel with a green concept is more successful and reduces waste as well as costs at the same time (Edirisuriya, Weerabahu and Wickramarachchi, 2018, Wiengarten, Fynes and Onofrei, 2013 Dieste et al. 2019, Rodrigues, Alves, and Silva, 2020). So, for sure, the logistics sector has positive and negative influences on society. The economic and social gains like a growing industry which generates jobs and most notably the fast flow of goods is very comfortable for the consumer and have positive contributions worldwide. On the other hand, the negative impacts on the environment, such CO2 emissions generated by the transportations of goods, are among the most concerns for the logistics sector. Rodrigues et al, 2020, no page). This implies that companies should feel a certain kind of pressure from society and legal standards by the government. In the future, warehouses will be more and more expected to be carbon-neutral, or even carbon positive, as the customer and legislation will demand a sustainable exposure of natural resources. Richards (2014) reports from a UK retailer who built a new distribution center intending to reduce its carbon footprint significantly. Early results show savings of 18% in energy costs, 45% in water usage, an overall reduction of 40% in CO2 emissions and a cost saving of GBP 250.000 per annum.” (Richard, 2014, p. 10) This example is a good indicator of savings for warehouse buildings considering new construction methods, techniques, and materials if they are being built up under ecological criteria and being lighthouse projects for further projects. These savings can be further improved by lean methods, which will help achieve more efficient transports of goods use of resources and environment during logistics operations. 4.3.4 E-Commerce Same Day Delivery – this term implies enormous logistic efforts on the delivery chains to fulfill this promise made to customers and the delivery chains. With the evolving development of material flow in the e-commerce business and affiliated increasing return advent, the grade of interconnectedness, automation, and system integration increases too. (Klempert, 2016). Online trade in Germany was growing by 23 % in 2020 (statista, 2021) representing a turnover of 96 Billion Euros. The phenomenon of e-commerce will continue to grow for business-to-business (B2B) as well as business-to-consumer (B2C) sectors. From a convenience point of view and under tremendous environmental pressure, grocery home shopping and delivery will also grow significantly. To this result came a study by Oliver Wyman (2020) about the future of food retailing in Germany. Amazon started with an express delivery service called Amazon Fresh which promises delivery for food and household goods within one hour. (Dobos, 2016) This will necessitate more fulfillment centres and returns processing facilities. Warehouses will be expected to be more efficient and cost-effective, with the likely closure of inflexible buildings and inefficient operations. (Richard, 2014, p. 105) As the market demands a higher scalable logistic performance, Würth Group invested in the further development of e-business solutions. In 2015 the turnover for e-commerce was growing by 17% and had reached 12% of the total turnover of Würth Group (Wöhrle, 2016c3). The EHI Retail Institute in Köln concludes in a study about the future of retail that there could be nine different scenarios and retail should play an active part in the digitalization process. The scenarios reach from the absolute end of the stationary retail up to a symbiotic scenario with huge flagship stores in the cities (urbanization) with a kind of adventure shopping for the customers to appraise the goods on-site and get it delivered by logistic partners of the retail, which will increase the complexity of logistics and also the return quote. (Bradl, 2016). 4.3.5 Industry 4.0 – Internet of Things (IoT) In 2020 12 to 50 billion devices will be connected, and the market for machine-to-machine communication (M2M) will rise by 40 – 50% as the price of communication modules has decreased by 1/5 compared to the last five years. (Kubach, 2014). According to IoT Analytics from 650 IoT-projects across all business sectors, most of them are realised in industry and smart city (22 and 20%) and just 4% in logistics. (Ciupek, 2016). One significant advantage will be predictive maintenance which allows ordering the needed spare parts already before it comes to a breakdown. Therefore, predictive maintenance can reduce the maintenance and breakdown times in detecting the broken part or wear of critical parts. One example is the Jungheinrich ISM Online software, an information system for truck management that offers a comprehensive fleet management. The system allows a detailed analysis of the trucks, detects truck crashes, and shows possible saving potentials with reports and performance figures. Consequently, the transparency and safety of the truck fleet in the warehouse will increase. (Jungheinrich, 2021) According to a white paper of KPMG (2016), it is no more sufficient to concentrate on short reaction times, high resource efficiency, and high quality to keep pace with faster product cycles, shorter lead times, and growing variants. In the factory of the future, the information and communication technology and the automation technology are fully integrated, and all sub-systems – even the not producing partners like sales partners, suppliers, OEMs, and customers are linked and merged into one system (KPMG, 2016). By introducing Internet of Things (IoT) technology, more than 40% of the respondents of a study by SAS expecting improved operational efficiency (Jones, A. et al., 2016). Many processes can be automatized, but there are many good reasons still trust in the human workforce. The human will never disappear because flexible systems are needed, and highly automated systems are not flexible! This means the human worker needs to be in place to use the strengths of both systems (Ciupek, 2015 Wöhrle, 2016). The digitalisation of the global supply chains will also mean establishing a partnership relationship between humans and machines in a future social networked industry . According to ten Hompel (2017), in the future – the social networked industry - machines and humans will work together as partners with equal rights. Kaspar and Schneider (2015) analysed the two approaches, Industry 4.0 and Lean, both seen as best practices for modern enterprises. They conclude that Lean and Industry 4.0 are not different from the basis as it seems from the first look and that they are aiming at the same goals and both bases on decentral control concept and they could complement one another. Finally, a lean organisation would be a good starting point and can be further optimised by Industry 4.0, and the same as Lean Industry 4.0 is evolutionary and not revolutionary like Lean is. Bick (2014) goes even further and states that I 4.0 critical needs Lean methods to decrease the complexity of dynamic systems and networks that companies face in these times. There is an ongoing integration between national economies and production networks on the macro level and on the micro-level the factory itself. According to Hoffmann (2014b), Lean and people will reach their borders as the processes respectively the system evolve from complicated to complex. Complicated problems are calculable but complex problems could be influenced but are consequently not calculable or manageable anymore. This is generally true, but it will still be the man who decides what processes and workflow should be digitized, and even artificial intelligence (AI) cannot solve the problem as this technology cannot give answers. AI can help to a certain extent to improve single operations and processes but not the whole system. An example would be Automated Guided Vehicles (AGV's) which will find their optimum route to the next source or trough. AI will also be able to decide which order should be released and performed due to available resources and criteria like shipping dates and priorities. So, all in all, it will be more or less a kind of assistance system but will not be able to replace the human being or will be a complete replacement for the Lean Philosophy. There will always be the need for human decision-making, and it is all the more important to use all disposable lean methods to achieve the best results and ongoing striving for continuous improvement. (Hoffmann 2014b). Kolberg and Zühlke (2015) conclude that Industry 4.0 or Smart factory phenomenon are complementary or even going hand in hand. If Lean Production is empowered by software and information technology, it enables a production system to evolve to a smart factory. Wanjari (2020) confirms in his case study that WMS and MES project implementation brings a substantial positive change in business performance. 4.3.6 Technology Trends Picking per data glasses called Pick by Vision (PbV) is a relatively new approach that promises time benefits and reduces error rates during the picking process. The glass is connected via Wi-Fi and has an integrated display that shows the operator the pick location, article information, and the quantity for the current pick order. The integrated barcode scanner and the WMS in the background check the correct storage location and the product code automatically while the operator has the hands free to pick the goods with both hands and put them carefully on the picking load carrier. (Klempert, 2016). Schnellecke is a service provider for the automotive industry and strives to be the best logistic service provider by 2020. One of the visions is a so-called plug' n play logistics, which allows them to roll out their services within a very short lead-time at any place in the world. To reach that state, it needs standardised processes and IT systems that were operated over the cloud. Another focus is automation and robotics to harmonize a continuous high-level quality with ergonomic workstations. An example is a new picking technology with augmented reality and Automated Guided Vehicles (AGV's) (Külps, 2016). After a three-month testing phase at the VW main factory in Wolfsburg, the 3D-data glasses are used by 30 workers, and it is planned to expand this technology throughout other business areas (Wöhrle, 2016a1). A different outlook on the future warehouse technology gives Professor Michael ten Hompel with a drone called Bin-Go , a shuttle system called RackRacer, and the cyber-physical system called Coaster (Asche and Hartbrich, 2016). Unmanned Aerial Vehicle (UAV) or drones are seen as the means of transport of the future. Examples of applications for drones in logistics already exist and will change logistics in the long term. (BVL, 2022) Examples are drones for stocktaking, surveillance or for transportation of goods and passengers. 4.3.7 Aging Workforce Since the beginning of 2015, Audi is testing the chairless chair at the sites in Ingolstadt and Neckarsulm. This exoskeleton worn at the back of the legs is fixed by a belt around the thigs and the hips. During many operations, the worker could sit in an ergonomic position instead of standing. (Wöhrle, 2016a) At the same time, supply chain partners have shortages of products, whereas e-commerce companies have shortages in personnel (Hasanat et al., 2020 Fernandes 2020). Reiser (2019) reports similar for the US market. In February 2019, the unemployment rate was at 3.8 percent, which is a historic low like in many European countries, but Germany and Netherlands have even unemployment rates below that. Meanwhile, e-commerce is proliferating, and this growth results in high demands on warehouse throughput and, of course, labor. Especially, companies with automated warehouses have difficulties finding qualified personnel to fill open positions and retain staff, which is finally hindering growth. (Reiser, 2019) 4.3.8 Summary This chapter about megatrends in logistics and warehousing is very technology-heavy, even the topic of the aging workforce. As already stated in chapter 4.2.1, all this technology bears the danger of focusing on new technology and ignoring human beings simultaneously, and the Lean Philosophy is about people and culture. Emmet (2005) summarised it already in the early 2000s' as follows. Warehousing can use all the best and efficient equipment, but the operations will fail without effective management. Even if the technical systems are the best, unmotivated people can still cause failures. Management is, therefore, ultimately all about people. Getting the best from people is the major and critical task for a business. (Emmet, 2005, p. 227). Nevertheless, technology and megatrends playing an important role and influence viable LW, and the following factors were derived. Insufficient toolset in terms of the functional scope of WMS KPI's in the warehouse are mostly related to performance quality and cost and do not consider soft factors which give hints regarding the morale and motivation of the employees and could be a good substitute in the sense of a logistic assistance system. The current trend for automation in warehouses bears the danger of over-engineer the processes – which is one form of the seven wastes - and does not care sufficiently about continuous improvement process anymore, which is fundamental in lean thinking. Logistics underlies legal actions and a certain pressure of the society to protect the environment and fulfill the new standard for green logistics . The labour bottleneck is getting a severe issue driven by a more technical working environment and risen expectations on the qualification and skill set of new and old” workers.

Über den Autor

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.

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