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Warehouse management and internal logistics planning and control are growing in importance. Nowadays, many methods have been developed in the areas of warehouse management and internal logistics planning and control. Internal logistics is essential in creating value and maximising profits by streamlining internal logistics tasks. As a key indicator of logistic processes, efficiently is set transport time. The article deals with the possibilities of improving logistics and warehousing using available methods with the smallest possible input capital and decreasing transport time. In the first part, the warehouse is reorganised, and lean methods such as Kanban and Milk run are set. The presented design is applied to the newly created hall. The result is improved processes and shorter transport times for material at the workplace and, ultimately, faster delivery of the finished product to the market and customer satisfaction. Scientific and more important for this study professional benefits consist in the application of mentioned methods. Benefits as a save the costs for the process and more straightforward adjust to external influences.

This paper investigates the industry practices regarding the combinative use of Industry 4.0 and lean tools in the manufacturing sector. Following review of the literature, a questionnaire survey was distributed among manufacturing professionals in organizations which have already adopted Industry 4.0 technology and lean manufacturing, with the aim to highlight the popular combinations of tools as seen in manufacturing practice and capture the perceived level of their contribution to operational performance. The survey results show that Real time data, IoT for data exchange, big data analytics, Cyber –Physical Systems (CPS), predictive algorithms and robots are among the most popular I4.0 applications used to support lean attributes like continuous flow, Kanban, standardised work, TPM and continuous improvement. It also emerges that although the beneficial impact of lean production across the respondents’ organizations is widely accepted, the perceived impact of Industry 4.0 tools is not as clear.

In the era of digitalization, electronic Kanban (e-Kanban) extends the traditional Kanban with additional data and information sharing that allows for more flexible and optimized inventory planning. The lack of automated fill level measurements for load carriers still hinders the full automation of the process. Our aim is to develop a self-learning e-Kanban system that automatically triggers replenishment orders using machine learning and data from low cost, autonomous sensor modules that measure the fill level of load carriers. This paper explains the concept and presents a first version of the mentioned sensor module that consists of an Intel Realsense sensor and an NVIDIA Jetson Nano. An evaluation is presented as well using small load carriers, which shows the suitability of the proposed method.

To become a world class organisation, the basic requirements of any manufacturing company are Cycle time reduction, lower manufacturing cost and minimal inventory. To compete in the digital and dynamic world, the lean and agile manufacturing play a vital role to uplift the production process. Lean manufacturing prioritise the value addition by eliminating the repetitive, null valued processes in the manufacturing cycle. Agile manufacturing supports optimization, standardisation and automation of the development processes. The purpose of Lean and agile manufacturing is the customer satisfaction with a cost-effective price. The role of lean and agile manufacturing is vital to maintain the optimum work in process inventory in the production flow. In the present work, the concept of lean and agile manufacturing is applied in the boiler component fabrication work, where the aim is to determine the factors affecting the Work-In-Process (WIP) inventory levels to meet the required demand for each product. The decision variables are identified and their effects are analysed. The analysis is focused on root cause of the problem, fundamental problems associated with the systems, implementation of Kanban, inventory cost, reorder point etc. The work provides methodologies to minimize the total WIP inventory across all elements of the boiler component.

Advanced technologies (e.g., distributed sensors, RFID, and auto-identification) can gather processing information (e.g., system status, uncertain machine breakdown, and uncertain job demand) accurately and in real-time. By combining this transparent, detailed, and real-time production information with production system physical properties, an intelligent event-driven feedback control can be designed to reschedule the release plan of jobs in real-time without work-in-process (WIP) explosion. This controller should obtain the operational benefits of pull (e.g., Toyota’s Kanban system) and still develop a coherent planning structure (e.g., MRPII). This paper focuses on this purpose by constructing a discrete event-driven model predictive control (e-MPC) for real-time WIP (r-WIP) optimization. The discrete e-MPC addresses three key modelling problems of serial production systems: (1) establish a max-plus linear model to describe dynamic transition behaviors of serial production systems, (2) formulate a model-based event-driven production loss identification method to provide feedback signals for r-WIP optimization, and (3) design a discrete e-MPC to generate the optimal job release plan. Based on a case from an industrial sewing machine production plant, the advantages of the discrete e-MPC are compared with the other two r-WIP control strategies: Kanban and MRPII. The results show that the discrete e-MPC can rapidly and cost-effectively reconfigure production logic. It can decrease the r-WIP without deteriorating system throughput. The proposed e-MPC utilizes the available transparent sensor data to facilitate real-time production decisions. The effort is a step forward in smart manufacturing to achieve improved system responsiveness and efficiency.

Lean Manufacturing is a philosophy of continuous improvement to eliminate waste. This paper is the result of a case study conducted in south India's textile industry. Although the concept of lean manufacturing has shown good results in continuous process industry, compared with discrete manufacturing industry it has not been extensively utilized. Process industry and particularly textile industry has highly inflexible automatic machinery with high volume/low product variety. This complexity of the textile industry renders the introduction of lean manufacturing strategies a challenge; hence, it has been taken up as a challenge to introduce lean techniques in a textile market. To enhance the processes we chose a mix of meaning stream mapping (VSM), 5S, kanban, kaizen, poka-yoke, and visual controls. Potential levels of accomplishment prior to and after lean adoption were demonstrated using radar diagrams. The findings of this study show that a thorough analysis of the operation, set-up and changeover time (CO), the use of color coding for volume-mix recognition, the use of kaizen and the consistency circles that inspire the workers are some of the different keys to an effective lean implementation in a textile industry.

In this paper, an attempt is made to evaluate the continuous improvement techniques using hybrid MCDM techniques under fuzzy environment. The objective of the paper is to demonstrate the selection of best continuous improvement technique using Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and VIKOR. Lean Continuous, 5S, Kaizen, Poka-Yoke, Jidoka (Automation), and Kanban (Pull System) are considered as six alternative continuous improvement techniques. Number of Defects, Level of waste elimination, Cost, effective use of resources, Lead time between order and product delivery, and Quality of product are considered as six main evaluation criteria. Under each main criterion, two sub criteria are considered. The weights of priority of main criteria as well as the sub-criteria are computed using Fuzzy-AHP whereas the evaluation ratings/ weights of priority of alternatives with respect to each sub criteria are determined using Fuzzy-VIKOR. Finally, by using the weights of priority of main criteria and the alternatives’ evaluation ratings, the overall priority weights of alternatives are determined. Based on these overall priority weights, the alternatives are ranked. From the findings of the research, it is concluded that the results are more practical and realistic.

Fish being a perishable material inclined to denaturation obliges extreme care methodically from the time of harvest till processing. Actions such as inappropriate handling trailed by growing food borne diseases have been the most common causes of food contamination. Escalating global consumer demands for higher quality has stood as a serious threat to the rising Surimi export market in the country, demanding a revamp of the quality essentials of the supplied raw material. Surimi produced from raw materials of inferior quality can lead to a multitude of consequences, the grander being the recall of the entire lot produced from the market triggering huge expenses for the producing industry. Although such events are highly undesirable, there has been a sheer need to decrease the likelihood of such mishaps. Applying traceability along the supply chain not only confirms a possible solution for the problem but also introduces a quality outlook in the Indian Surimi supply chain. A precise technique of improvising the current system would be through information technology (IT) investment for restructuring the Indian Surimi supply chain to global standards and refining quality. This study analyses the supply side of the Indian Surimi supply chain using Value stream mapping (VSM) as a tool tracked by the use of Kanban’s to increase visibility for enhancement of quality and customer satisfaction.

The objective of this research is to establish an approach to select the best performing production control strategy for a Closed-Loop Supply Chain (CLSC) system with stochastic supply and demand. To test the operational performance of several pull-type production control strategies, a simulation-based methodology is applied to serial lines with variable processing times. The strategies experimented are: Hybrid Extended Kanban CONWIP (HEKC-II) with modifications, Hybrid Kanban CONWIP (HKC), Dynamic Allocation Hybrid Extended Kanban CONWIP (DNC HEKC-II) special case, Dynamic Allocation Hybrid Kanban CONWIP (DNC HKC) and the newly postulated Intelligent Self-Designing Production Control Strategy (ISD). The successful implementation and the highly positive experimental results for the new strategy provided a major shift of the Pareto performance frontier, simultaneously minimising the conflicting objectives of reducing customer demand backlog (by over 80%) and reducing the WIP (by over 22%) relative to an optimised HKC strategy, the control group.

The increase in the offer of product variety towards customization is a trend in the industrial sectors of high competitiveness. In this context, mass customization is sought based on flexible manufacturing systems. Performance indicators of cost, resource utilization, inventories or rate of production hold a trade-off dependent on the system design and demand. Quantifying alternative flow control manufacturing systems through simulation allows comparing their performance and its suitability to different production scenarios. From a portfolio of furniture products, their manufacturing processes are determined, and processing times estimated. The operations of the manufacturing cell for wood components of furniture factory are developed by discrete event simulation. The model includes the conditions of a push system and a pull system using Kanban between the work stations. Variation of batch size and product mix demand is also established with a common set of conditions for one-year simulation run. The design of experiments and analysis of variance provides the quantification of the main influence factors on the desired performance indicators. Conclusions and future research opportunities are brought on their overall trends and trade-offs.

Production optimization can be done on different levels, ranging from improving individual machines, over organizational aspects like Kanban, to optimizing the overarching production planning. The last approach may inherit the greatest potential. Still, it is also the most challenging since it requires a holistic systems engineering approach. One of the main challenges is the lack of an overall optimum. Wiendahl represents the conflict of objectives in the polylemma of production. The paper presents a practical framework for the optimization of production management processes. We derived it from a variety of corresponding projects. It describes how the conflict of objectives can be analysed systematically and a reasonable operational status can be derived. Questions of medium and short-term production planning are addressed. This includes the definition of the analysis objective, the analysis of the initial state and the optimization. The phases are each described with the help of examples.

The production of customized products in small batch sizes represents a major challenge for the industry. Especially the assembly environment is affected due to less possibilities for economical automation, thus manual assembly remains an important part of production. Assistive systems for manual assembly aim at minimizing the challenges associated with a customer driven production. These systems support human workers by providing manufacturing information, highlighting material boxes or identifying assembly errors. To do so assistive systems need to be user-centered and allow a flexible adaption to new products or assembly processes. With our approach, we present a concept that uses RFID technology and sensory input to enable an intelligent material supply system. This enables an automatic identification and data capture (AIDC) for assistive systems. Existing materials at the working station, including position and numerical quantity can be recognized and matched with the production order. Advantages and potential outcomes for assistive systems, like autonomous pull request for material (Kanban), are discussed in this paper. Furthermore, we describe the structure and implementation of our concept using the example of the manual working station of SmartFactoryKL. The development of the system, the achieved improvements as well as identified challenges for assistive systems will be presented. The prospects for further developments and their potential will be discussed.

Since the mixed-model assembly lines are highly adopted in the automobile industry, the part feeding process has become a critical challenge. Therefore, in this paper the dynamic part feeding scheduling problem under a Kanban system is studied, which aims to optimize a productivity-related objective (the throughput of the assembly lines) and a cost-related objective (the total delivery distance of the automatic guide vehicles (AGVs)) simultaneously. A comprehensive part feeding process considering the part feeding tasks generation, the loading, sequencing and dispatching problems is analyzed and modeled. To properly solve the problem, this study proposes a hybrid fuzzy-neural-based dynamic scheduling method, integrating the Self-organizing maps (SOM) with the Fuzzy c-means (FCM) algorithm and the knowledge base (KB). The SOM is adopted to pre-cluster the system status and optimize the initial clustering centers, then the FCM is availed to guide the clusters, so as to improve the clustering performance simultaneously. Computational experiments are conducted to evaluate its scheduling performance in a dynamic manufacturing environment and verify its superiority over the benchmark algorithms. The method allows decision makers to select more rational scheduling schemes based on their decision impacts in both productivity and part feeding costs and the real-time status of the assembly lines.

Lot splitting is an important approach for shops that compete on short delivery times. Similarly, such shops can benefit from load-limiting order release mechanisms that balance workloads and regulate throughput times. Yet few studies have examined the combined effect of lot splitting and load-limiting order release. We use simulation to assess the combined effect of lot splitting and P aired-cell O verlapping L oops of C ards with A uthorization (POLCA), an important load-limiting order release mechanism in the context of time-based competition. The experimental design includes different lot sizes, lot transfer policies, and POLCA quanta, i.e. the limit on the size of jobs represented by a single POLCA card. Lot splitting improves performance if lots can proceed independently as this ensures the quick replenishment of queues at downstream stations. However, we find that enforcing the synchronization of all lots that make up a job at every routing step leads to a deterioration in performance. This extends previous research, which appears to have overemphasized the positive effects of lot splitting. Meanwhile, although POLCA cards were originally used to represent lots, we demonstrate that using cards to represent a certain amount of workload can improve percentage tardy performance. This may also have resonance with other card-based solutions, including kanban.

In this study, a new pull production control strategy called Basestock-Constant Work-in-Process (B-CONWIP) is proposed. It is used to control the flow of materials and information in balanced assembly production systems. This proposed control strategy uses one type of authorization cards called CONWIP card that limits the work-in-process (WIP) in the whole system. It has been applied in a single-product and a mixed-product assembly system balanced by two efficient Genetic algorithms introduced in literature. The performance of this control strategy is compared with another pull production control strategy called Basestock Kanban CONWIP (BK-CONWIP), which is a very promising production control strategy found in literature. The proposed strategy has two control parameters, CONWIP authorization cards and basestock levels while BK-CONWIP has three control parameters Kanban authorization cards, CONWIP authorization cards and basestock levels. The comparison is based on three performance measures average system WIP, percentage of satisfied customer demand (service level) and WIP variation between workstations. The performance of the proposed strategy B-CONWIP and BK-CONWIP is mainly similar in both types of assembly systems when mean demand rates are low with respect to mean service rates with the proposed strategy being easier to control and optimize. On the other hand, when mean demand rates are high with respect to mean service rates; B-CONWIP is preferable if service level is more important, while BK-CONWIP is preferable if WIP level is more important. Regarding WIP variation, it mainly depends on the efficiency of the balancing approach. The more efficient the balancing approach, the less WIP variation. Treating demand as lost instead of backordered results in decreased average system WIP and does not affect service levels in both PCSs. It is also shown that S-KDP is more flexible in dealing with situations of variable product mixes than d -KDP because control parameters can be used by any product which minimizes the effect of the unbalanced systems.

Following a well-established track record of success in other domains such as manufacturing, Kanban is increasingly used to achieve continuous development and delivery of value in the software industry. However, while research on Kanban in software is growing, these articles are largely descriptive, and there is limited rigorous research on its application and with little cohesive building of cumulative knowledge. As a result, it is extremely difficult to determine the true value of Kanban in software engineering. This study investigates the scientific evidence to date regarding Kanban by conducting a systematic mapping of Kanban literature in software engineering between 2006 and 2016. The search strategy resulted in 382 studies, of which 23 were identified as primary papers relevant to this research. This study is unique as it compares the findings of these primary papers with insights from a review of 23 Kanban experience reports during the same period. This study makes four important contributions, (i) a state-of-the-art of Kanban research is provided, (ii) the reported benefits and challenges are identified in both the primary papers and experience reports, (iii) recommended practices from both the primary papers and experience reports are listed and (iv) opportunities for future Kanban research are identified.

As continuous improvement tools evolve, so does the complexity and the size of data. With the ubiquity of data and the scale of machine automation, abilities for rapid decision making and handling of ever increasing complexity of system become necessary. Kanban is on the robust tool to visualize any process. In this paper, we propose a cloud Kanban framework that enables deployment of process excellence. The study addresses two research questions: (1) how can a robust cloud-based Kanban decision support framework work for a service industry, particularly in operations? (2) how can an evolutionary algorithm, specifically Ant Colony Optimization (ACO), augment a cloud-based Kanban decision support framework?

Due to its assumed inherent inability to manage custom-engineered parts and components, the Kanban system has traditionally been disregarded in high mix, low volume “engineer-to-order” environments. However, elements of the Kanban system have proven their worth in other turbulent, non-manufacturing environments, such as software development. In this paper, we draw on two case studies from the Maritime sector where Kanban boards and cards have been introduced for the execution phase of shop orders in manufacturing. Initial results have been exceptional, with 50% reduction of lead-time realized in both cases. © 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All right reserved.

The lean manufacturing approach is one of the process improvement and business development philosophies that can be applied in all sectors. In this context, lean construction enables the development of common applications by combining the production sector and the construction sector under the name of lean in order to improve and develop construction processes . This study was carried out in order to help the creation of a lean construction system by selecting the most appropriate lean techniques to determine and eliminate the waste in construction processes and to reduce costs by increasing the efficiency of the processes. Within the scope of the study, the wastes arising in the construction processes and the selection of lean production techniques that can eliminate these wastes were discussed as a multi-criteria decision making problem. In this problem wastes were determined as decision criteria and lean techniques were determined as solution alternatives. The problem structure consists of 8 main criteria that are about overproduction, waiting, transporting, inventory, operation, movement, production and work accidents, 24 sub-criteria, namely, construction waste and 5 alternative lean techniques such as 5S Technique, Just in time production, Kanban, Total productive maintenance and Visual Management. In the solution phase of the problem, the criteria weights and importance order of wastes in the processes were obtained by using SWARA method, lean construction techniques were evaluated by using Fuzzy VIKOR method under fuzzy environment. As a result of the evaluations, on one hand among the 24 criteria in the construction processes, faulty construction due to the lack of integration between design and production and improper processes due to the operational mistakes made by the employees were determined as the most important waste and on the other hand Kanban and Visual Management were determined as the most suitable alternative lean techniques for the construction processes. According to this result, Kanban that can convey the demands of all the elements in the lean system to the previous process with all the details in line with their needs and Visual Management that can visualize all the work done in the system as much as possible should be used in construction processes primarily.

Industry 4.0, referred to as the “Fourth Industrial Revolution”, also known as “smart manufacturing”, “industrial internet” or “integrated industry”, is currently a much-discussed topic that supposedly has the potential to affect entire industries by transforming the way goods are designed, manufactured, delivered and payed. This paper seeks to discuss the opportunities of Industry 4.0 in the context of logistics management, since implications are expected in this field. The authors pursue the goal of shedding light on the young and mostly undiscovered topic of Industry 4.0 in the context of logistics management, thus following a conceptual research approach. At first, a logistics-oriented Industry 4.0 application model as well as the core components of Industry 4.0 are presented. Different logistics scenarios illustrate potential implications in a practice-oriented manner and are discussed with industrial experts. The studies reveal opportunities in terms of decentralisation, self-regulation and efficiency. Moreover, it becomes apparent that the concept of Industry 4.0 still lacks a clear understanding and is not fully established in practice yet. The investigations demonstrate potential Industry 4.0 implications in the context of Just-in-Time/Just-in-Sequence and cross-company Kanban systems in a precise manner. Practitioners could use the described scenarios as a reference to foster their own Industry 4.0 initiatives, with respect to logistics management.

Providing a desired level of customer service in the business is an important part of logistics management. The role of logistics is to provide transport right material in the right quantities and the right quality to the right place. The problem arises when harmonization logistics requirements. This article focuses on solving the problem of increasing the level of customer service through effective material transport, handling and storage. The first part focuses and compares different types of warehouses and the order picker's inventory management technologies. The second part is devoted to logistics and supply. Warehouse management and transport of the material is connected with tractive control system that reacts flexibly to changes in customer requirements. Authors in solving based on the results of realized survey of the current situation in enterprises in the described areas.

Characterization of two known card-based control policies as adaptive.Two novel adaptive card-based control policies are proposed.Complete comparative evaluation of nine adaptive card-based control policies. This article is about adaptive production control policies based on Kanban and CONWIP. First, it is shown that the Extended Kanban and the Generalized Kanban control policies, which have not been considered up to now in the relevant literature, actually fall within the category of adaptive card-based production control policies. Moving further, two novel adaptive production control policies are proposed, the Adaptive Generic Kanban and the Adaptive Extended Kanban. The proposed policies along with Extended Kanban and Generalized Kanban are compared in a simulation study to five existing adaptive approaches for controlling Kanban and CONWIP systems. It is noted that a comparative evaluation of these five existing adaptive policies is also absent from the relevant bibliography. The set of nine policies is tested in a tri-objective optimization problem, i.e. minimizing mean Work-In-Process, mean finished goods inventory and mean length of backorders queue under three different demand patterns. A multi-objective evolutionary algorithm is used to find optimal or near-optimal parameters for the control policies, and the resulting Pareto fronts are compared in terms of several metrics. In this experimental trial, the Extended Kanban, the Generalized Kanban and Adaptive Extended Kanban policies achieve the highest ranking.

Packaging is essential in logistics processes. All products consumed in a supply chain from fresh berries to large containership-parts are packed during their transportation and storing processes. Often plastics are used as a basic component for the bins. These synthetic materials are produced from crude oil. After their use plastic packaging is often burned to receive thermal energy. To measure and analyse the environmental impact a life cycle assessment can be carried out. In this paper the assessment is done for a Kanban bin made out of sunflower granulate. A typical supply chain situation is simulation. Different system boundaries are used. The production and the use/ maintenance phase are analysed with the help of a framework. The highest impact on the environment is during the use phase. The transportation and the recycling phase can be neglected in terms of the environmental impact. Using a sunflower-granulate the emissions during the production phase can be reduced. The impact is less strong considering a life cycle process.

Aimed at maximizing project value while reducing waste and cost, the lean construction (LC) approach was formally and successfully introduced to the architecture, engineering and construction (AEC) industry in 1993. Although LC has rapidly developed since that time, it was not applied to a Chinese construction project until 2005. However, due to insufficient knowledge and poor execution, this first attempt at lean construction in China was inadequate. The aim of this study was therefore to discover if the Chinese construction industry has since discovered how to use lean practices to maximize project value, shorten the project schedule, improve project quality, and reduce waste. This was achieved by conducting a case study of a LC project in Suzhou, China. The case study revealed that implementation of lean practices during the project, including Last Planner System (LPS), Kanban system, Just-In-Time (JIT), prefabrication, Internet of Things (IoT), quality and safety management, and continuous improvement, all contributed to the improvement of project performance. To supplement the case study and to provide insights on the differences between Chinese and international LC, interviews with project stakeholders and a questionnaire survey of global lean experts were conducted. Results indicated that interviewees and survey respondents both held the view that project waiting times and defects can be greatly reduced through the implementation of LC, and that improvement of construction workflow along with project productivity and quality were the two most valuable benefits of using lean practices; there was also a consensus that lack of trust and the abilities of stakeholders are the biggest challenges.

We consider WIP-controlled line production systems with constant processing times.For a given QoS, both CONWIP and DBR outperform a Kanban.A DBR system needs less buffer capacity than or at most equal a CONWIP system.In general, a CONWIP system outperforms a DBR system under the same QoS.Under the certain condition a DBR system outperforms a CONWIP system. We compared three types of WIP-controlled line production systems with constant processing times such as Kanban, CONWIP (constant work-in-process) and DBR (drum-buffer-rope). Based on the observation that such WIP-controlled line production systems are equivalent to m-node tandem queues with finite buffers under communication blocking policy, we applied a max-plus algebra based solution method for the tandem queue to evaluate their performance. Within our knowledge, this research is the first attempt to apply an exact solution method for comparing all three WIP-controlled line production systems at a time. Six-node numerical examples were also used to demonstrate the proposed analysis. The numerical results can be generalized and also provide some insights in designing production systems under certain limited condition.

The optimization of performance in SMEs networks becomes an important challenge in a globalization context. The dynamism of the market and the uncertainty of the demand force the enterprises to reconcile efficiency and flexibility. It has been proven that dynamic cellular manufacturing systems allow to attain both objectives. However, no bridge has been built between enterprise networks and the use of DCMS. A literature review allowed to highlight the inherent elements of the two concepts and to draw a conclusion on their complementarity. The main objective of this study was to determine the effects of the use of DCMS and product modular design on the network performance, using a design of experiments (DOE) and a discrete event simulation. A real case study was conducted to validate the model. The results show that, in a turbulent environment, standardization via the use of a product modular structure and a Kanban system may lead to a successful implementation of DCMS. Multidisciplinary employees and a high suppliers’ reliability were also important in ensuring the optimization of the total production, WIP, lead time (Makspan), and delay. The case-study demonstrated that improvement projects such as 5S, improvement of quality and planning system and training and involvement of sales and engineering departments led to the successful implementation of DCMS. The attitude toward improvement was also important and mainly manifested by the support and commitment of top management, the involvement of the employees, the desire of improvement, the listening and active participation of employees and managers, a constant communication, as well as clear and well-defined objectives

Manufacturing companies have been forced to rethink their management and operations strategies due to the growing demand for greener products and services. To support these initiatives, the Lean and Green (L&G) approach has gained increasing attention from academic and industry. However, according to the literature in the field not all Lean practice has a positive environmental impact. In addition, there is a lack of empirical research on L&G to understand the catalyzers and trade-offs between both paradigms. Therefore, this study attempts to fill this gap by assessing the applicability of Lean Manufacturing (LM) tools and investigate how Lean impacts Green performance in a real-world company case. This research paper assesses the integration of Lean & Green in the job shop of a Brazilian company and is supported by a discrete-event simulation (DES) model. Green analysis regarding water, energy and raw material consumption are performed for every single operation. Environmental and production variables are simultaneously evaluated, and the environmental impacts resulting from the implementation of the Lean practices and tools, such as Kanban, are also discussed. While the outcomes of the research reveal a positive correlation between Lean & Green on performance indicators, they also substantiate a trade-off on water consumption. The empirical study along with the simulation-based analysis demonstrate that generalizations such as “Lean is Green” must be carefully revisited and also emphasize the importance of Lean & Green relationship in the improvement of manufacturing processes.

Despite the fact that the fields of pull type production control policies and condition-based preventive maintenance have much in common contextually, they have evolved independently up to now. In this investigation, an attempt is made to bridge the gap between these two branches of knowledge by introducing the single-stage Kanban system with deterioration failures and condition-based preventive maintenance. The formalism of continuous time Markov chains is used to model the system and expressions for eight performance metrics are derived. Two important, from a managerial perspective, constrained optimization problems for the proposed model are defined where the objective is the simultaneous optimization of the Kanban policy, the preventive maintenance policy and the inspection schedule under conflicting performance criteria. Multiple instances of each optimization problem are solved by means of the augmented Lagrangian genetic algorithm. The results from the optimization trials coupled by the results from extensive numerical examples facilitate the thorough investigation of the system’s behaviour.

Production authorisation cards and basestock levels are lower in shared policy.The shared policy responds to demand variations quicker than the dedicated policy.BK-CONWIP has a higher flexibility than the alternatives in terms of WIP control.BK-CONWIP is the best performer of the three pull control strategies examined. The consideration of demand variability in Multi-Product Lean Manufacturing Environment (MPLME) is an innovation in production system engineering. Manufacturing systems that fail to recognise demand variability generate high Work-In-Process (WIP) and low throughput in MPLME. In response to demand variability, organisations allocate large quantities of Production Authorisation Cards (PAC). A large proportion of PAC results in a high WIP level. However, the Shared Kanban Allocation Policy (S-KAP) allows the distribution of PAC among part-types, which minimises WIP in MPLME. Nevertheless, some existing lean manufacturing control strategies referred as Pull Production Control Strategies (PPCS) that have shown improved performance in single-product systems failed to operate S-KAP. The recently developed BasestockKanban-CONWIP (BK-CONWIP) strategy has the capability of minimising WIP while maintaining low backlog and volume flexibility. This paper investigates the effects of erratic demand on the performance of PPCS in MPLME. It is shown that S-KAP BK-CONWIP outperforms other PPCS. Finally, it is feasible to design quick-response PPCS for MPLME under erratic demand.

Product mix influences the performance of pull production control strategy in multi-product manufacturing systems. The complexity of product mix on the performance of a manufacturing system is primarily based on the characteristics of the demand and production control strategies. Demands are mainly characterised by volume and product-type while production control strategy is characterised by material release time, part flow, inventory control and throughput times. In multi-product systems, pull production control strategy operates dedicated or shared Kanban allocation policy. This paper examines the performance of the Generalised Kanban Control Strategy (GKCS), Extended Kanban Control Strategy (EKCS) and Basestock Kanban-CONWIP (BK-CONWIP) control strategy operating Shared Kanban Allocation Policies (S-KAP) or Dedicated Kanban Allocation Policies (D-KAP) for a healthcare parallel/serial assembly line with setup times. A simulation based multi-objective optimisation technique was adopted to examine the effect of different product mixes on the strategies and policies. A ranking and selection technique for multiple systems was used to screen the performance of the strategies. It was shown that product mix variability in a system influence the inventory levels of the pull control strategies examined. However, the performances of the strategies vary with strategies operating S-KAP having better inventory control than strategies operating D-KAP. Similarly, BK-CONWIP outperformed its alternatives.

The competitiveness in the globalized environment highlights the importance of becoming more efficient in the execution of the company's operative and administrative processes in order to improve the level of customer service, delivery times, quality of products or services, as well as to optimize resources. The great advantage of implementing integrated logistics activities as a strategy to achieve this is undeniable. This paper, therefore, presents the methodology and the benefits obtained, which, with properly forecasted demand, aggregate planning methodology and the synchronization of some lean manufacturing techniques using tools like JIT (Just In Time) and SMED (Single Minute Exchange of Die), make the enterprise more competitive in delivery lead time, improve customer service level and reduce inventory. This case study involved some functional areas like Demand Planning, Materials Planning, the Manufacturing and Production Departments and the Warehouse Area. The principal objective of this research is to create a continuous flow of the stamped parts, from the Stamped Area to the final Assembly Line; in order to avoid sending the materials to the warehouse as currently happens.

Since the past two decades, small, medium and large automotive industries have grown rapidly and globally in Malaysia in line with the increasing of demand from customers. To increase market share and sustain in industry, most of the companies continuously applied world-class manufacturing techniques such as Lean Manufacturing, Toyota Production System, Just-in-Time (JIT), Kanban, Kaizen, Six Sigma and others. In order to achieve world class manufacturing status such as on-time delivery, high quality and high production efficiency, an effective material handling system is necessary to support production processes. Based on observation at a JIT automotive assembly line of a local automotive manufacturer in Shah Alam, it was found that the existing material storage system used was bulk storage called as wire mesh and trolley. Also, the material handling activities were run without referring to any standard or procedure. Therefore, the aims of this case study are to design a new storage system for an automotive component which is Air Cleaner by using computer aided design software, CATIA V5R20 and to evaluate its’ effectiveness by using a computer aided manufacturing software, DELMIA Quest. Improvement will be made on the existing material handling system by introducing new standard poly-boxes and a gravity flow rack system for material handling activities. The results obtained from the computer simulation were compared to the existing performance of the line. Inventory level has managed to be reduced by 74% while space utilization reduced by 18.18%.

The Lean Production paradigm has become the major approach to create highly efficient processes in industry since the early 1990s. After the sudden end of the Computer Integrated Manufacturing (CIM) era, which finally was doomed to fail due to its unrulable complexity of the required automation technology, the Lean approach was successful because of its high effectiveness by reducing complexity and avoiding non-value-creating process steps. Today, the term Industry 4.0 describes a vision of future production. Many people are at least skeptical or even hostile towards this new approach. This position paper gives an overview over existing combinations of Lean Production and automation technology, also called Lean Automation. Furthermore, it discusses major Industry 4.0 corner stones and links them to the well-proven Lean approach. Examples of combining both are smart watches for supporting the Andon principle or Cyber Physical Systems (CPS) for a flexible Kanban production scheduling.

Lean production is highly appreciated in the manufacturing world. Which directly helps to integrate human and machines. Sustainable approach, making continues improvement, value adding services all are the main objective of a lean production system. But since Industry 4.0 emerging as new trend in the manufacturing group. It works with the help of ICT and CPS will help traditional manufacturing to integrate with Industry 4.0. Which will be further lead a smart network, product and smart machines. ICT will integrate with the entire value chain to make a Smart factory which will be the future of intelligent manufacturing. This paper will describe the existing lean production and implementation of Industry 4.0. Moreover, a plot will be drawn between drawbacks of lean and advantages of industry 4.0. Combining both and the role of CPS, elimination of Kanban and new trends of implementation will be explained.

A production control system (PCS) can be considered an information-processing organization (IPO). The performance of different production control systems has been studied intensively. However, their decision-making efficiency has not drawn much attention. The amount of information in a production control system can lead to a delay in decision-making. This paper considers the effect of product position information on decision-making. We use information entropy to measure the amount of position information in products and find that there are different amounts of position information in MRP, KANBAN, and CONWIP. Then, we compare the decision-making time delay among the three production control systems across identical organizational structures for information processing. We conclude that the production control system with the smallest amount of information spends the least amount of time in decision-making.

Lean leadership could be the missing link between toolbox lean and a sustainable continuously improving organization. More and more enterprises realize that they have so far basically focused on the visible parts of lean production systems. Although process optimization with the various methods like kanban, 5S, SMED, FIFO and many more is very effective to achieve short term improvements, after a few years, the lean programs of many enterprises do not meet the expectations anymore. The common approach can be explained by using the 4P Model. It consists of 4 levels that are all necessary for a sustainable lean implementation. The levels are: philosophy (long-term thinking), process (eliminate waste), people and partner (respect, challenge and grow them) and problem solving (CIP and learning). All these terms are well- known. However, most enterprises merely focus on process. Eliminating waste in all processes has been preponderantly adopted, whereas the other 3Ps, the “invisible” parts of lean, are less easy to adopt but equally important for the sustainable implementation. Lean leadership addresses all 4Ps and provides a methodical system for the sustainable implementation and continuous improvement of lean production systems. It describes the cooperation of employees and leaders in their mutual striving for perfection. By now, many authors have identified the need for a lean leadership but only few holistic concepts exist. Especially lower and middle management lacks some clear advices and rules for lean leadership implementation. Therefore, some indicators for successful lean leadership were deduced from literature, study results, and practical experiences of lean implementation. The indicators were found in advices given on successful lean implementations, but particularly in mistakes and shortcomings. After reformulating the indicators into requirements for leaders, they were assigned to the five principles improvement culture, self-development, qualification, gemba, and hoshin kanri. These requirements shall help executives in realizing lean leadership.

Short setup time is an essential element for the effective implementation of many lean pillars, i.e., JIT, and Kanban. Most of the current setup reduction methodologies are based on Shingo's Single Minute Exchange of Dies (SMED) that suggests the conversion of internal setup operations to external operations. However, the conventional SMED approach - as proposed by Shingo - does not possess a systematic approach to accomplish this conversion. Thus, a new approach is proposed in order to aid the process engineers in implementing SMED. The proposed approach is based on the conventional SMED, but also it incorporates Multiple Criteria Decision-Making Techniques (MCDM) to the third implementation phase. The MCDM techniques used in this work are Analytical Hierarchal Process (AHP), Preference Selection Index (PSI) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The proposed approach provides a systematic procedure for selecting the best setup technique among the available alternatives, and takes also into consideration other factors that affect the decision-making process; including: cost, energy, facility layout, safety, life, quality and maintenance. A real example of PVC industry is used to exemplify the approach. The results demonstrate the capability of the proposed approach in setup time reduction, which in turn will improve machines' utilization, and increase the productivity and flexibility of the whole facility.

We consider a production-inventory system that consists of n stages. Each stage has a finite production capacity modelled by an exponential server. The downstream stage faces a Poisson demand. Each stage receives returns of products according to independent Poisson processes that can be used to serve demand. The problem is to control production to minimize discounted (or average) holding and backordering costs. For the single-stage problem (n=1), we fully characterize the optimal policy. We show that the optimal policy is base-stock and we derive an explicit formula for the optimal base-stock level. For the general n-stage problem, we show that the optimal policy is characterized by state-dependent base-stock levels. In a numerical study, we investigate three heuristic policies: the base-stock policy, the Kanban policy and the fixed buffer policy. The fixed-buffer policy obtains poor results while the relative performances of base-stock and Kanban policies depend on bottlenecks. We also show that returns have a non-monotonic effect on average costs and strongly affect the performances of heuristics. Finally, we observe that having returns at the upstream stage is preferable in some situations.

This research deals with balancing a mixed-model U-line in a Just-In-Time (JIT) production system. The research intends to reduce the number of stations via balancing the workload and maximizing the weighted efficiency, which both are considered as the objectives of this research paper. After balancing the line and determining the number of stations, the labor assignment policy should be set. In this study, it was assumed that there are two types of operators: permanent and temporary. Both types can work in regular and overtime periods. Based on their skill levels, workers are classified into four types. The sign at each work station indicates types of workers allowed to work at that station. An alert system using the hybrid kanban systems was also considered. To solve this problem, a Simulated Annealing algorithm was applied in the following three stages. First, the balancing problem was solved and the number of stations was determined. Second, workers were assigned to the workstations in which they are qualified to work. Following that, an alert system based on the kanban system was designed to balance the work in the process inventory. This was achieved by defining control points based on the processing time and making control decisions to minimize the number of kanban cards. In the proposed SA algorithm, two methods for the temperature cooling schedule were considered and two methods were defined for determining the number of neighborhood search. The initial temperature was considered equal to the cost of the initial solution to reach the convergence situation as soon as possible. Five problems were solved in small size using the GAMS software. The results obtained from the GAMS software were compared with those obtained from the SA algorithm to determine the performance difference. The computational results demonstrated that the SA algorithm is more consistent with the answers obtained. Also seven large scale problems were solved. The results showed that the SA algorithm still have better reliability. To show the efficiency of the proposed SA algorithm, an axel assembly company was studied. To satisfy demands and reduce backlogging, a mixed model assembly line was designed for this case study. The results showed that the mixed model assembly line designed using the SA algorithm had good efficiency.

In this paper, a single-stage single-class kanban controlled manufacturing system is considered, where the problem is quoting accurate lead times for orders that are generated by an MRP system. Order release mechanism as in classical MRP is sensitive to the changes in the lead time according to the concept of lead time syndrome. The objective is to establish a cost effective lead time quoting procedure. The problem is modeled as a two-dimensional Markov chain, and it is solved explicitly by using matrix geometric techniques. Comparative analysis is done between static and dynamic lead time quoting procedures, and significant cost benefits of the dynamic procedure are shown under various scenarios. Guidelines for setting design parameters such as the number of kanbans and the frequency of updating the lead time are provided through numerical tests.

Assembly lines managed by means of lean production philosophy are usually characterized by workstations with inline stock areas, supplied by means of items contained in a larger supermarket zone. Furthermore, inline components necessities are usually showed by means of the use of kanbans. In this work, the number of kanbans and the number of carriers serving the line are computed by means of Erlang-C approach, in order to minimize a total cost function obtained as the sum of an estimation of cost of inline stock and of cost of refilling operations. Specifically, the Erlang-C approach is adopted since assures fast re-design of the system when variations in input data occur. Finally, a real-life case study in a company manufacturing items for the automotive market field is presented in order to highlight the approach potentialities when alternative scenarios are studied.

There is good evidence from experience reports and other literature that the lean flow concepts of on-demand, value-based scheduling and limited work-in-progress are highly effective in many instances of software development. The question remains, however, if they are equally applicable to the systems and enterprise engineering found in large or complex system environments. This paper builds on previous conceptual work to describe specific applications of the concepts to support coordination of systems engineering activities within large-scale system acquisition, development and evolution. Using a surrogate environment derived from the complex interactions of IT, embedded systems, and human activities in a large multi- facility hospital system, we provide examples of how integrated kanban-like constructs can be created at each systems engineering level from an individual project through the complete capabilities portfolio.

This paper is intended to formulate the so-called production lead time problem as the problem of throughput optimization under a constraint on production lead time. A solution is provided for serial lines with Bernoulli machines and infinite buffers. Specifically, analytical formulas are derived for raw material release rates, which guarantee the desired lead time, while maximizing the throughput. Based on this solution, a method for selecting design parameters of kanban- and CONWIP-controlled systems, which ensure the desired lead time, is provided.

This think-piece will sketch GVCs in East Asia through trade statistics and narrative descriptions obtained by factory visits. It will consider such issues as weaknesses arising from the ‘Kanban’ (‘just-in-time’) production system, the impact of third-country (migrant) labor, and the implications of the TPP for East Asian GVCs.

Introduction – Medication error is very undesirable in healthcare because it has a great risk of causing worsening patient condition. There are many factors that can lead to medication errors. One of them is small difference in mentioning, the absence of sufficient symbol for trade name, caused by similar volumes, sizes, colors, shapes, and letters from the labels. The risk of medication errors can be eliminated by direct methods such as the use of symbols and words, which are clear and easily distinguishable. In addition, the packaging of dosage and drug distribution systems is performed carefully to address medication errors.Methodology – The method we apply was similar because it was basically a part of the Lean Six Sigma (LSS) project at KMC as a whole. The DMAIC method applied in KMC for this project.Results - On April 2015, we found documentation error and time error in 15 medical record documents recording 24 drug services. Documentation error was recorded at 37.5% or 9 drug service error. On May 2015, we recorded three drug services in 9 medical records. On June 2015, we found 21% documentation error in 8 medical record documents examined. Discussion - The application of LSS at KMC provides positive effects on the reduction of medication errors. Indeed, medication errors can be derived from the drug factory itself or its writing that is not clear from doctors as well as the use of the wrong methods in medical testing. Even so, through the initial steps of DMAIC and methods such as 5S, layout redesigning, doctor habit observations, and kanban, the risk of medication errors can be reduced.

We present a pull system that uses a new approach to facilitate material control and scheduling in a disassembly environment and is called the multi Kanban system for disassembly (MKSD). Within the MKSD is an approach to optimize operation and mitigate supply chain risk factors as well. We also compare the performance of MKSD to its “push” counterpart. Various scenarios are explored using a case example. For the scenarios, the assumptions, input data and results are presented. The study clearly demonstrates the effectiveness of the multi Kanban system over the push system.

This paper discusses a single-item, multi-stage, serial Just-in-Time (JIT) production system with stochastic demand and production capacities. The JIT production system is modeled as a discrete-time, M/G/1-type Markov chain. A necessary and sufficient condition, or a stability condition, under which the system has a steady-state distribution is derived. A performance evaluation algorithm is then developed using the matrix analytic methods. In numerical examples, the optimal numbers of kanbans are determined by the proposed algorithm. The optimal numbers of kanbans are robust for the variations in production capacity distribution and demand distribution.

Research highlights? Kanban number and size represent the inventory levels of a JIT system, and there is a trade-off between them. ? An integrated multiple objective genetic algorithm (MOGA) based system is developed to determine the Pareto-optimal kanban number and size. ? The proposed system integrates simulation models, experimental designs, regression models, and MOGA. ? This research finds that some of the Pareto-optimal solutions have better performance than the current kanban number and size used in the case company. In a just-in-time (JIT) system, kanban number and size represent the inventory level of work-in-process (WIP) or purchasing parts. It is an important issue to determine the feasible kanban number and size. In this research, an integrated multiple-objective genetic algorithm (MOGA) based system is developed to determine the Pareto-optimal kanban number and size, and is applied in a JIT-oriented manufacturing company to demonstrate its feasibility. In the integrated system, a simulation model is built to simulate the multi-stage JIT production system of the company. Then an experimental design of different kanban numbers and sizes for different production stages is applied to test the production performances. Based on the simulation results, regression models are built to represent the relationships between the kanban numbers of different production stages and the production performance. These regression models are then used in genetic algorithms to generate the performance for chromosomes. Finally, the proposed multi-objective genetic algorithm (MOGA) based system uses the generalized Parato-based scale independent fitness function (GPSIFF) as the fitness function to evaluate the multiple objectives for chromosomes and used to find the Pareto-optimal kanban number and size for multiple objectives, i.e., maximizing mean throughput rate and minimizing mean total WIP inventory. A comparison in the performance of the proposed system with that of the current kanban number is conducted to demonstrate the feasibility of the proposed system.

Modern day industry is becoming leaner by the day. This demands engineers with an in-depth understanding of lean philosophies. Current methods for teaching lean include hands-on projects and simulation. However, simulation games available in the market lack simplicity, ability to store the results, and modeling power. The goal of this research is to develop a virtual simulation platform which would enable students to perform various experiments by applying lean concepts. The design addresses these deficiencies through the use of VE-Suite, a virtual engineering software. The design includes user-friendly dialogue boxes, graphical models of machines, performance display gauges, and an editable layout. The platform uses laws of operations management such as Little's law, economic order quantity (EOQ) models, and cycle time. These laws enable students to implement various lean concepts such as pull system, just-in-time (JIT), single piece flow, single minute exchange of dies (SMED), kaizen, kanban, U-layout, by modifying the process parameters such as process times, setup times, layout, number, and placement of machines. The simulation begins with a traditional push type mass production line and the students improve the line by implementing lean techniques. Thus, students experience the advantages of lean real time while facing the real life problems encountered in implementing it.

This paper reviews the literature regarding variations of the kanban system, i.e. the aim is to study only the modified kanban systems. Thirty two different systems were studied and classified according to six categories: the publication year of the paper, the number of original characteristics conserved in the variation, the operational differences between each variation and the original kanban system, the advantages in relation to the original kanban, the disadvantages in relation to the original kanban, and the way those systems were tested. A brief summary of each adaptation is shown, integrating the scattered efforts undertaken by the authors with the aim of improving the kanban system and adjusting it to the new and/or distinct necessities of the production systems. Our analysis of the papers, using the proposed classification method, provides useful insights on the anatomy of the literature about variations of the kanban system. It was found that, among other topics, there is a great difference between the quantity of theoretical and practical proposals.