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This article focuses on implementing the Single Minute Exchange of Dies (SMED) method within the case study company, a local subsidy of a global producer of hygiene products. Such research was not yet done in the area of Eastern Slovakia, nor was it done for the area of hygiene produce production. The article lists unique specifics taken during the process. The results exceeded the preliminary management expectation, where a changeover time reduction by 30% was achieved. From the managerial perspective, this demonstrates that the SMED method is a mandatory approach for companies struggling with frequent and long changeover times.

In this paper, we introduce a mixed-integer linear program for a shift scheduling problem in a German potash mine. In particular, we consider a short-term (work shift) production scheduling problem, where drill-and-blast mining operations have to be assigned to machines and workers simultaneously. Since we deal with several sequence-dependent setup, changeover, and removal times, TSP-variables are used in the mathematical program to determine the processing-sequence of the operations on each worker and each machine, respectively. In addition, several mining-specific requirements are taken into account to obtain a solution that can be put into practice. Computational experiments are conducted on problem instances of realistic size derived from real-world data. The results show that our new mixed-integer linear formulation outperforms both existing solution procedures for the problem at hand.

Nowadays, mixed-model assembly lines (MMALs) are extensively applied to manufacture different products with no need for the changeover of the whole lines to satisfy the diversified preferences of c...

In recent years, to attain a competitive edge, merely optimizing the production efficiency is no longer the whole story that the manufacturing enterprises concentrate on. Instead, the increasing energy costs are driving manufacturing enterprises to seek an energy-oriented approach further to improve the overall performance of the production systems. Therefore, an opportunistic maintenance policy under energy and quality constraints is developed for a degrading batch production system in this paper. First and foremost, the degradation process of the production system is modeled using the Levy-type processes, meanwhile, the concept of the multielement-dependent degradation model was first put forward to describe the energy and quality degradation in production systems during the work period. Secondly, the degradation constraint threshold, energy constraint threshold, and quality constraint threshold are developed to determine the maintenance groups which include the machines that require two types of maintenance, preventive and corrective. Subsequently, in order not to interrupt the batch production activities, the changeover time between every two batches is regarded as an energy saving window to perform maintenance actions for the integrated maintenance groups. Thirdly, an energy-oriented integrated model that optimizes the total cost rate in consideration of energy and quality is developed, and the optimal maintenance combination scheme can be obtained by the Monte Carlo method. Finally, a numerical example is used to prove the effectiveness of the proposed policy.

In automotive paint shops, changes of colors between consecutive production orders cause costs for cleaning the painting robots. It is a significant task to re-sequence orders and group orders with identical color as a color batch to minimize the color changeover costs. In this paper, a Color-batching Resequencing Problem (CRP) with mix bank buffer systems is considered. We propose a Color-Histogram (CH) model to describe the CRP as a Markov decision process and a Deep Q-Network (DQN) algorithm to solve the CRP integrated with the virtual car resequencing technique. The CH model significantly reduces the number of possible actions of the DQN agent, so that the DQN algorithm can be applied to the CRP at a practical scale. A DQN agent is trained in a deep reinforcement learning environment to minimize the costs of color changeovers for the CRP. Two experiments with different assumptions on the order attribute distributions and cost metrics were conducted and evaluated. Experimental results show that the proposed approach outperformed conventional algorithms under both conditions. The proposed agent can run in real time on a regular personal computer with a GPU. Hence, the proposed approach can be readily applied in the production control of automotive paint shops to resolve order-resequencing problems.

The success in developing a metal forming process is relied heavily on the design of a preform to reduce the final forming load at the final step. The design of the preform is considered a big burden of a process designer. Currently, the automotive companies try to design components which can cover a wide range of car models, but only changing a few dimensions to accommodate different models. However, each product is still considered a single product during the process design. Therefore, if only one preform can cover a variety of products, the process design could speed-up and gain more benefits in the production. In this research, a technique to design preform for various product models was proposed. The aim of this technique is to develop generalized common preforms by utilizing the same part configuration/shape but different dimensions in some areas to reduce the number of preform and process design time. This technique is composed of two steps: (a) classification of product groups and (b) determination of the common tool for producing the common parts. This technique was applied to the cold forging process to produce various models of automotive pulleys. The results show that the number of preforms was reduced by almost 70%, and the die changeover time was approximately saved by 75 min per shift (8 h/shift), and the capacity was gained by 1800 pieces per shift without generating any product defects.

Due to the increasing greenhouse gas emissions and the energy crisis, the manufacturing industry which is one of the most energy intensive sector is paying close attention to the improvement of environmental performance efficiency. Therefore, in this paper the automated assembly line is balanced in a sustainable way which aims to optimize a green manufacturing objective (the total energy consumption) and a productivity-related objective (similar working load) simultaneously. A comprehensive total energy consumption of each processing stage was analyzed and modeled. To make the model more practical, a sequence-based changeover time and robots with different efficiencies and energy consuming rates are considered and optimized. To properly solve the problem, the proposed novel optimal solution takes the well-known MOEA/D as a base and incorporates a well-designed coding scheme and a problem-specific local search mechanism. Computational experiments are conducted to evaluated each improving strategies of the algorithm and its superiority over two other high-performing multi-objective optimization methods. The model allows decision makers to select more sustainable assembly operations based on their decision impacts in both productivity and energy-saving.

This paper proposes an integrated multi-product production planning and distribution allocation in the supply chain network, including the detailed production sequences in each production line for a dairy manufacturing. The models are designed for manufacturers that produce multi-products. One of the concerns of the multi-products manufacturers is the sequence-dependent changeover times and costs that occur when switching from one type of product to another. The models are developed into two-stages due to different levels of decisions. The first stage models the supply chain network that determines the optimum production planning for each product type on each production line, delivery schedule, and inventory planning for the entire supply chain simultaneously to maximize the total profit. Sequentially, based on the optimal production planning, detailed production schedules are then optimized in the second stage of the model with minimizing total setup costs as the objective. The result shows that the proposed models significantly reduce the total cost and consequently increase the annual gross profit.

This project was carried out at a company in the electric mobility sector, which manufactures chargers for electric vehicles, specifically in the wiring section. The main objective of the developed work was to improve the production processes in order to enhance responsiveness to the growing demand. After analyzing the processes in the section, the objectives were outlined to enable the improvement of some practices in the production department, such as the ones related to the organization of the raw material supermarket, as well as the calculation of the wiring consumption by chargers, and the implementation of a production control system. After the improvement actions were implemented, it was possible to observe a 14,9% reduction in the changeover process of the cable cutting process; weekly wiring consumptions were estimated, and procedures were defined to generate orders of raw material and supply to the workstation, which led to the elimination of stock shortages. In addition, worker autonomy increased and production downtime was reduced.

The present work was carried out on a cork company that is dedicated to the production of floating floors and its aim was to reduce by 15% the time it takes to perform series changes in one cutting line. The research methodology used in this work was the action research methodology. The methodology consisted of 5 phases, as follows: 1st - historical data collection and setup filming, 2nd - footage analysis and conduction of informal interviews with workers, 3rd - flow, Gantt, and spaghetti charts creation and making of an action plan based on the waste and improvement opportunities identified in video analysis, 4th - validation with the line workers of the new operating mode created with the Single Minute Exchange of Dies (SMED) tool and communication to the Maintenance department about their role in this project, 5th - making and placement of plasticized cards on the cutting lines to ensure that new operating mode is followed and carrying out the actions identified in the action plan. The obtained results are very positive in the cutting line: after the implementation of the new guidelines in the Final Finishes 2 (AF2), there was a 2 minutes increase in the changeover compared to the time initially observed, but being now performed by only two workers and not by three, as initially occurred.

Many process control problems with complex qualitative specifications cannot be addressed via conventional control design methods. Examples of such specifications include logic specifications expressed in the design of start-up, shut-down, changeover, and emergency shutdown operating procedures. In recent years, it has been shown in the control systems and computer science communities that symbolic models provide convenient and powerful mechanisms to synthesize controllers enforcing such qualitative specifications. The use of symbolic models reduces the synthesis of the controllers to a fixed-point computation problem over a finite-state abstract system. In this paper, after explaining the notion of approximate bisimulation for incrementally globally asymptotically stable ( δ -GAS) nonlinear control systems, the construction of approximately bisimilar symbolic models for such systems is presented. Then synthesis of time-optimal symbolic controller for this class of systems is performed based on results from the computer science literature. As a benchmark chemical process control problem, an approximately bisimilar symbolic model is constructed for a safe changeover process. Then a symbolic controller is designed and it is refined to a controller to be applied to the original process. Simulation results show the effectiveness of the symbolic controller. Although the construction of the symbolic model may be complex, the synthesis of the controller in a finite-state space is fast and most importantly the error bounds are adjustable as design parameters.

PurposeOver the past years, collaborative robots have been introduced as a new generation of industrial robotics working alongside humans to share the workload. These robots have the potential to enable human–robot collaboration (HRC) for flexible automation. However, the deployment of these robots in industrial environments, particularly in assembly, still comprises several challenges, of which one is skills-based tasks distribution between humans and robots. With ever-decreasing product life cycles and high-mix low volume production, the skills-based task distribution is to become a frequent activity. This paper aims to present a methodology for tasks distribution between human and robot in assembly work by complexity-based tasks classification.Design/methodology/approachThe assessment method of assembly tasks is based on the physical features of the components and associated task description. The attributes that can influence assembly complexity for automation are presented. Physical experimentation with a collaborative robot and work with several industrial cases helped to formulate the presented method.FindingsThe method will differentiate the tasks with higher complexity of handling, mounting, human safety and part feeding from low-complexity tasks, thereby simplifying collaborative automation in HRC scenario. Such structured method for tasks distribution in HRC can significantly reduce deployment and changeover times.Originality/valueAssembly attributes affecting HRC automation are identified. The methodology is presented for evaluating tasks for assigning to the robot and creating a work–load balance forming a human–robot work team. Finally, an assessment tool for simplified industrial deployment.

Lightweight and load-adapted products offer opportunities for savings in terms of material usage and environmental pollution. Additionally, the requirements of Industry 4.0 are changing industrial manufacturing from mass production to mass customization and on-demand manufacturing. These aspects are accompanied by new challenges and motivate the development of manufacturing systems with higher flexibility. Flexible processes allow the realization of several families of parts on the same system with shortened changeover time. For this purpose, the novel forming process “flexible roller beading” was developed, which enables the production of sheet metal profiles with customizable, height-variable cross-sections. The manufactured height development of the profile is not tool-constrained and can be adapted individually to the part application loads. By this level of flexibility, new design requirements can be satisfied in sheet metal profile manufacturing. Furthermore, semi-finished products can be produced, which potentially reduce the necessary expenses and expand the process limits of downstream forming processes. With the presented work being the initial introduction of “flexible roller beading”, the operating principle is presented. As a key aspect, the feasibility of the novel process is shown. Therefore a flexible roller beading manufacturing system fulfilling the necessary kinematic requirements of the forming process is developed and experimental tests are carried out. Additionally, an FE model of the process is created and validated by experimental comparative tests. From the results of experimental and numerical investigations, defect types and process limits are determined, which are the bases for further process optimization towards the industrial suitability of flexible roller beading.

This paper demonstrates how it is possible to combine SMED with Centerlining in complex production environments with numerous changes of format, product, raw materials and tools. This research proposes a methodology involving an initial application of Centerlining and, once the machinery and the process are stable, the subsequent implementation of SMED. Furthermore, it aims to show that it is possible to achieve improved output and reduced machinery changeover time while ensuring that the effect achieved by SMED is more stable. This increases the organizational advantages with respect to the implementation of SMED without prior application of Centerlining. The most important overall conclusion is that a successful application of SMED must always be accompanied by another type of tool or technique to maximize the results of its application. And, as presented in this work, one technique that enables significant improvements to SMED is the application of Centerlining.

Nowadays, dynamic products life cycles and increase in the number of product variants have led to reduction in demand per variant. This modern trend is in contrast with the high production volume of manufacturing processes such as injection molding, since they are commonly employed for mass production due to their long changeover time. Traditional rigid molds do not seem to be able to cope with the current industrial and market challenges. Flexible and reconfigurable molding processes, such as the discrete pin tooling systems and changeable molds, appear to be a promising choice for achieving manufacturing economic sustainability. They represent an effective way to save resources and reduce labor costs and setup times. This paper explores the evolution of molds used in manufacturing, from the old models to the current reconfigurable ones through a state-of-the-art analysis of academic research and solutions implemented by industry. Conclusions and insights are presented.

The impacts of the static synchronous compensator (STATCOM) on the traditional loss of excitation (LOE) protection are investigated in this article. To do a comprehensive study, a common and realistic excitation system is developed for the generator by employing the phase-domain model of the synchronous generator accessible in the real-time digital simulator. Using such a model, the LOE phenomenon is realistically studied in accordance with IEEE Standard C37. 102-2016, while the generator dynamics along with the LOE relay performance are investigated through different types of partial and complete LOE events. It is shown that in the presence of STATCOM, two major impacts on the generator and its LOE protection can be expected: 1) it imposes an additional time delay on the relay to detect the LOE failures, which depends on the generator initial loading and the type of LOE failure and 2) it might lead the generator to reach a new stable operating point without experiencing a loss of synchronism condition, during an improper changeover from automatic voltage regulator to manual voltage regulator operating mode. The related consequences for both of the impacts are discussed in this article, and some solutions are suggested to deal with the probable negative aspects.

The purpose of this research is to determine the practicality of a prospective reform of the Moroccan money market's interbank rate within the context of the worldwide shift of reference indices. By analyzing 351 days of quotations, we were able to acquire an optimistic result using the chosen approach, which includes regulated variations that keep the compound rate relatively stable in comparison to other rates. The findings can be used as a benchmark for future maturities. It is worth noting, however, that the compounding strategy does have certain drawbacks. This is the most often used strategy among market participants due to its simplicity in terms of theoretical foundations and openness. The primary shortcoming of the suggested model is its lack of predicting. The methodology is based on previous day's data, with an eye toward the past, which complicates the changeover given IBOR rates' future-oriented methodology. This research project is designed to act as a starting point for future revisions to the ideas made in the body of this research.

Playing computer games has made a noteworthy changeover to our age's playing style by making the more significant part of them to stick to it. In this way, tackling those diversion issues is a fascinating subject that requires cautious area explicit component definition and an adaptable amusement hypothesis look calculation. So, in this manner, we picked an amusement flappy feathered creature, which includes exploring a winged animal through a bundle of obstacles (pipes) and influence it to make due for quite a while in a steady progression. In addressing this issue, we employed the use of such RL (reinforcing learning) by defining the correct component and after that through the proper activities at every amusement occasion, contributes the pre-emptive specialist who has gotten from a model of CNN (convolutional neural system) which acts as a decent defining product while removing elements from their previous feed previews. We extend a general framework to learn essential highlights of diversion and deal with the problem as appropriate.

The performance indicator, Overall Equipment Effectiveness (OEE), is one of the most important ones for production control, as it merges information of equipment usage, process yield, and product quality. The determination of the OEE is oftentimes not transparent in companies, due to the heterogeneous data sources and manual interference. Furthermore, there is a difference in present guidelines to calculate the OEE. Due to a big amount of sensor data in Cyber Physical Production Systems, Machine Learning methods can be used in order to detect several elements of the OEE by a trained model. Changeover time is one crucial aspect influencing the OEE, as it adds no value to the product. Furthermore, changeover processes are fulfilled manually and vary from worker to worker. They always have their own procedure to conduct a changeover of a machine for a new product or production lot. Hence, the changeover time as well as the process itself vary. Thus, a new Machine Learning based concept for identification and characterization of machine set-up actions is presented. Here, the issue to be dealt with is the necessity of human and machine interaction to fulfill the entire machine set-up process. Because of this, the paper shows the use case in a real production scenario of a small to medium size company (SME), the derived data set, promising Machine Learning algorithms, as well as the results of the implemented Machine Learning model to classify machine set-up actions.

Manufacturers are poorly equipped to manage product transition scenarios, when moving from one product to another. Most tools consider a mature system, yet during transition and ramp up disturbances and inefficiency are common. The traditional methods, using centralised planning and control structures are too rigid and often resort to simple dispatch heuristics in this highly dynamic environment. Distributed systems have been proposed to leverage their self-organising and flexible traits to manage highly volatile and complex scenarios. Anarchic manufacturing, a free market based distributed planning and control system, delegates decision-making authority and autonomy to system elements at the lowest level; this system has previously been shown to manage job and flowshop style problems. The system has been adapted to use a dynamic batching mechanism, where jobs cooperate to benefit from economies of scale. The batch enables a direct economic viability assessment within the free market architecture, whether an individual machine should changeover production to another product type. This profitability assessment considers the overall system state and an agent’s individual circumstance, which in turn reduces system myopia. Four experiments, including a real-world automotive case study, evaluate the anarchic manufacturing system against two centralised systems, using three different ramp-up curves. Although not always best performing against centralised systems, the anarchic manufacturing system is shown to manage transition scenarios effectively, displaying self-organising and flexible characteristics. The hierarchical system was shown to be impeded by its simplifying structure, as a result of structural rigidity.

The objective of this work was to analyse the cost and the benefit of extending the useful life of bandsaws by improving their wear resistance in a parawood saw mill. Changeover of worn bandsaw causes downtime 15 minutes. Saw blade change frequency is two to four times per shift, at a sawn rate of 90-120 cubic feet per day. Reduced wear bandsaws can be accomplished by flame hardening, which would reduce grinding cost and losses from changeover downtime. This article therefore analyses scenarios of rubber wood processing plants in Thailand with between nine and sixty sawmills per plant and 300 working days per year. The annual scenarios analysis, based on saw blade grinding and additional flame hardening cost, has an annual fixed cost and variables cost. Implementing the flame hardening increases the costs by THB 80 319.53 to 1 021 737.99 per year. The benefits in this study indicate that reduced wear on bandsaws by implementing a flame hardening process in rubber parawood factories is economical, with benefits in the range of THB 643 577.34 to 11 446 939.60 per year. Die doel van hierdie studie is om die koste en voordeel van verlengde, bruikbare bandsaagleeftyd te ontleed. Die verlenging in bruikbare leeftyd is behaal deur hul slytasieweerstandigheid te verbeter. Dit neem 15 minute om 'n geslyte bandsaaglem te ruil. 'n Lem word gewoonlik twee- tot vier keer per skof geruil teen 'n saagtempo van 90 tot 120 kubieke voet per dag. Verbeterde slytasieweerstandigheid is bewerkstellig deur vlamverharding. Hierdie verbeterde saaglemme verminder slypkoste en verliese as gevolg van produksiestilstand. Hierdie artikel ontleed verskeie rubberhout meulens in Thailand, elkeen met tussen nege en sestig meulens per aanleg en 300 werksdae per jaar. Die jaarlikse scenario-ontleding, geskoei op saaglem slyp- en vlamverhardingskoste, het 'n jaarlikse vaste koste. Die vlamverharding verhoog die kostes met THB 80,319.53 tot THB 1,021,737.99 per jaar. Hierdie studie toon dat die verminderde slytasie van die bandsaaglemme inderdaad ekonomies is, met voordele wat wissel tussen THB 643 577.34 tot THB 11 446 939.60 per jaar.

Work holding devices are a crucial part of the component that are custom made for a particular part or situation. Over the past decade, there in increase in mass production and has increased the demand for forged components. Wheel hubs being the major component in an automotive responsible for attaching the wheel. The work holding was the primary issue of the machining operation to be confronted. The objective of this paper describes the detailed definition of work holding devices and also identifies several benefits that are connected with the use of work holding in manufacturing that includes increase in production rate and cost reduction. Interchangeability and accuracy of machining parts which at most eliminates the need for inspection and quality expenses. It also describes the changeover from the traditional job holding technique towards the fixtures that can be controlled through CNC machines or VMC machines itself and serves the necessary purpose with minimal errors as there is not much of interference of human operators. Adapting this kind of simple and effective mechanism in fabrication and manufacturing sector drastically reduces the cost of labor and cycle time, thereby increasing the quantity and quality of production. This fixture assists the forged work piece used for the wheel hubs of an automobile for drilling and tapping at required positions. The forged component already manufactured needs to be drilled as per the drawings with respect to its orientation to perform the mentioned operations. To undergo the operation a special Colette system was designed and manufactured.

Thin-walled parts with double-sided features are widely used in many industrial sectors but their machining is particularly time consuming and challenging. Collaborative machining is a new paradigm in the development of industrial 4.0. It can potentially revolutionize the existing thin-walled part machining methods, leading to higher productivity, flexibility and sustainability. For this end, this paper introduces a novel concept with dual parallel kinematic machines (PKMs) collaboratively performing synchronized and asynchronized cutting and support from both sides of a thin-walled part, without changeover/re-clamping of the workpiece. Compared to the conventional single-sided machining, this study shows that static and dynamic performances of the workpiece are significantly improved under the dual PKM collaborative operation. A case study of milling a thin-walled part with double-sided features was conducted by PKMs under three comparative strategies, namely, double-sided synchronized milling, alternative single-sided milling, and sequential single-sided milling. Experimental results show that the novel double-sided synchronized milling strategy by dual collaborative PKMs produced the best dimensional accuracy and satisfactory surface quality due to the improved static stiffness and dynamic performance, and balanced deflections. More importantly, a two-fold greater productivity has been achieved as the novel strategy doubles the material removal rate while eliminating the cumbersome in-process steps used in conventional single-sided machining.

Purpose The balancing of robotic weld assembly lines has a significant influence on achievable production efficiency. This paper aims to investigate the most suitable way to assign both assembly tasks and type of robots to every workstation, and present an optimal method of robotic weld assembly line balancing (ALB) problems with the additional concern of changeover times. An industrial case of a robotic weld assembly line problem is investigated with an objective of minimizing cycle time of workstations. Design/methodology/approach This research proposes an optimal method for balancing robotic weld assembly lines. To solve the problem, a low bound of cycle time of workstations is built, and on account of the non-deterministic polynomial-time (NP)-hard nature of ALB problem (ALBP), a genetic algorithm (GA) with the mechanism of simulated annealing (SA), as well as self-adaption procedure, was proposed to overcome the inferior capability of GA in aspect of local search. Findings Theory analysis and simulation experiments on an industrial case of a car body welding assembly line are conducted in this paper. Satisfactory results show that the performance of GA is enhanced owing to the mechanism of SA, and the proposed method can efficiently solve the real-world size case of robotic weld ALBPs with changeover times. Research limitations/implications The additional consideration of tool changing has very realistic significance in manufacturing. Furthermore, this research work could be modified and applied to other ALBPs, such as worker ALBPs considering tool-changeover times. Originality/value For the first time in the robotic weld ALBPs, the fixtures’ (tools’) changeover times are considered. Furthermore, a mathematical model with an objective function of minimizing cycle time of workstations was developed. To solve the proposed problem, a GA with the mechanism of SA was put forth to overcome the inferior capability of GA in the aspect of local search.

This paper presents a mathematical programming model for dynamic cell formation to minimize changeover-related costs (i.e., machine relocation costs and machine setup cost) and inter-cell material handling cost to cope with the volatile production environments in apparel manufacturing industry. The model is formulated through findings of a comprehensive literature review. Developed model is validated based on data collected from three different factories in apparel industry, manufacturing fast fashion products. A program code is developed using Lingo 16.0 software package to generate optimal cells for developed model and to determine the possible cost-saving percentage when the existing layouts used in three factories are replaced by generated optimal cells. The optimal cells generated by developed mathematical model result in significant cost saving when compared with existing product layouts used in production/assembly department of selected factories in apparel industry. The developed model can be considered as effective in minimizing the considered cost terms in dynamic production environment of fast fashion apparel manufacturing industry. Findings of this paper can be used for further researches on minimizing the changeover-related costs in fast fashion apparel production stage.

Organizations are increasingly required to have a high level of quality and flexibility in production. In order to remain in the market and become competitive, the working methods practiced must be reliable and efficient. The present project sought the improvement of an equipment of the cork industry by introducing a variation, through the application of Lean methods. The equipment under study performs the union of a cork stopper to a capsule, which is done by gluing it with hot-melt glue. The amount of production makes the changeover activity a regular process. The method followed in this work was the study and collection of information on the Lean production philosophy and its application in the cork industry. The working conditions of the assembly machine were also analyzed in order to find opportunities for improvement. Thus, the tool used was the Value Stream Mapping (VSM) technique in order to acknowledge the processes that really add value to the product. The SMED (Single Minute of Exchange of Die) methodology was applied in a way to reduce the downtime caused by tool changes, and a reduction of 43% in total changeover time was obtained. It was also created an A3 model to monitor the entire development of the SMED project, Finally, the OEE (Overall Equipment Efficiency) calculation was implemented as an indicator of overall equipment efficiency, in order to improve the monitoring of possible deviations during production. The feedback also proves that lean tools are a powerful method to get solid returns without large investments.

Every industry has a growing need to improve quality, output and voice of the customer satisfaction. The purpose of this paper is to exhibit the achieved results after implementing SMED tools at a certain production line in the Romanian pharmaceutical industry. Completing Changeovers between products on a certain packaging machine using Single Minute Exchange of Dies (SMED) technique offers the possibility to shorten the machine downtime, increasing the final output. Implementing Lean Manufacturing philosophy, major Changeover time at the bottleneck process decreased by 30% in 12 months. Along with the economic benefits from the SMED implementation, process quality, standardization and teamwork have been improved.

Nowadays, the manufacturing industry is increasingly globalized and competitive, where the quality, cost, variety and fulfillment of delivery deadlines are fundamental factors for the customer. Therefore, to better meet these demands companies need to find strategies to make their processes more flexible and efficient. In the modern industrial environments the elimination of waste in order to concentrate as much as possible on value-added activities often leads to a reduction in the downtime of equipment. In addition, product diversification and reduced orders lead companies to have to optimize their setup processes on the equipment to produce the different required references. Making the setups faster is to keep the machine with less downtime, while converging with the need to decrease non-added value operations. One way to achieve the reduction of setup changeover time is through Single Minute Exchange of Die (SMED). The goal in this paper is to perform a brief literature review regarding the SMED methodology which is addressed throughout several scientific fields, but most often in scientific publications in the fields of engineering and management. As a result, a widespread number of research papers from distinct authors are utilized to achieve the objectives of the current study. The time range for this study is from 2007 till 2018 and the selection includes journal, conference proceedings and book chapter papers. A descriptive analysis of the results is then made through charts and tables which are utilized to enrich the content and to offer a practical and simple presentation.

Implementing mass customization can inevitably lead to a large product variety, which makes the assembly process in mixed-model assembly lines (MMALs) very complex. In this paper, the concept of product variety induced changeover complexity, as one major source of uncertainty in mixed-model assembly, is proposed. Three types of changeover complexities measured using information entropy are presented. As the negative impact of changeover complexity on the performance of a MMAL can be reduced by selecting a suitable model sequence, a bi-objective car sequencing problem taking it into account is proposed. The problem is aimed at finding a model sequence with the minimum number of violating sequencing rules as a primary criterion, and the minimum level of total changeover complexity as a secondary criterion. A lexicographic approach based on ant colony optimization (ACO) is applied to solve the problem. Computational experiments show that both objectives can be effectively addressed using the presented ACO algorithm.

Die casting is a complex process performed in harsh working environments. Driven by cost and environmental pressure, die casting, as one of the most energy-intensive manufacturing processes, has received increasing attention on enhancing energy efficiency toward greener and more sustainable manufacturing. Energy efficiency evaluation is a starting point for energy audits and analysis of energy-saving scenarios, while complex production conditions in the die casting workshop (e.g. product changeover, technology improvements, and degradation of equipment performance) require even higher real-time and dynamic performance of energy efficiency evaluation. To this end, this paper proposes a multi-level energy efficiency evaluation framework based on fog-cloud computing. Accordingly, real-time parameter identification models and dynamic energy efficiency evaluation method are proposed. An industrial case study of die casting workshop has demonstrated the feasibility and effectiveness of the proposed approach. The results reported that the overall equipment effectiveness and energy utilization ratio of die casting units increased by 3% and 7%, respectively, and energy consumption per kilogram of the die casting workshop was reduced by 7.9%, showing its great potential in identifying energy efficiency improvement opportunities.

A Changeover is the set of operations required to switch from producing one product to another and it includes both setup and cleaning operations. Changeovers are especially critical for multi-product environments where flexibility, time and quality are key requirements of the manufacturing system. A range of environmental and economic impacts occur during changeover operations and quite frequently the magnitude and extend of these are not fully captured by manufacturing companies. However, information gathered from the literature and factories suggest that these impacts could drastically reduce the sustainability performance of companies through creating waste streams. Furthermore, reduced economic and environmental performance of the companies impairs social and industrial desire to achieve sustainable systems. This research focuses on how companies can develop capabilities to evaluate and monitor their changeover performance, as well as understanding the causes of these impacts and how can they be mitigated. In this paper, the underlying factors and root causes of changeover impacts will be discussed. Results from the case studies suggest that, it is possible to capture changeover losses by using a mass balance approach. In addition to this, twelve factors were identified as the main influencers of changeover performance and further analysis of these twelve factors provided three root causes that determines the changeover performance. Identification of these factors and causes was expected to help industry to improve their changeover performance by highlighting the key areas to focus on and hence improve firms' sustainability performance.

Short cycle time of customer orders is crucial for companies to achieve mass customization and quick response. However, the complicated and stochastic environment, especially the exist of setup times, makes it extremely challenging to optimize the efficiency of a system. In this study, stochastic customer orders are scheduled to minimize their expect cycle time with the consideration of setup times. Customer orders arrive dynamically, and each order requires multiple product types with random workloads. These workloads will be assigned to a set of unrelated parallel machines to be processed. Particularly, for each machine, setup times are required whenever there is a product type changeover, and the lengthes are both machine- and product type-dependent. This paper intends to minimize the long-run expected order cycle time by proper policies including workload allocation and type sequencing. The impacts of product type sequence and workload variance are evaluated through theoretical study and several analy...

In this paper, we examine the set-up problem at semiconductor assembly and test facilities in a multi-machine, multi-tooling environment. Our primary objectives are to minimise the number of shortages of key devices and to maximise weighted throughput over a 2–5-day planning horizon. When a machine set-up is called for three components must be taken into account: tooling, package size and flow. Each in turn imposes increasing set-up times, ranging from a few minutes to half a day. To balance system efficiency with meeting customer demand, a hierarchical approach is taken. Priority is first given to set-ups that can process (hot) lots that reduce demand shortages. Next, changeover time is factored into the decision. Here, priority is given to the component that takes the least amount of time. Our model determines machine set-ups, lot assignments and lot sequences using a greedy randomised adaptive search procedure. The results indicate that reducing set-up times can reduce hot-lot shortages by up to 6.6% o...

The industry faces a trend of fabricating a product with high-variety and short life cycles since the change of consumer behaviors. The quality control becomes critical. In milling process, surface roughness is key quality characteristic measured by an off-line method. The off-line measurement is time consuming. Therefore, online surface roughness monitoring systems, which can eliminate the measurement time and enhance the productivity, have gained popularity for machining. However, to accurately construct the system, a large amount of data and time for off-line training and modeling are required, which make the system not suitable for a high-variety job shop production. It is necessary to develop a method without large data and off-line training and modeling. Therefore, a Grey online modeling surface roughness monitoring (GOMSRM) system is proposed in this study by utilizing the Grey theory GM(1, N) with bilateral best-fit method, which requires less data and no training time to perform the online modeling surface roughness monitoring system. The ability of an online modeling makes the system flexible to monitor different types of products. The model could be built during each changeover process of the milling, which can significantly eliminate the time of training in advance used by other off-line modeling methods. The results show the GOMSRM system can accurately predict the surface roughness. The comparison between the GOMSRM system and the system developed by a neural network shows the GOMSRM system has better accuracy and fewer samples for modeling.

Dr. Shingo's SMED (single minute exchange of dies) methodology is the most well-known method for changeover time reduction using both simple methodological solutions and tool/design changes. Simplification and standardization are the main technique of SMED to make the changeover process independent from personal experience. However, in plastic injection molding, process parameter setting after changing the molds totally depends on the varied expertise levels of setup experts. The number of available setup experts in a shift dictates the number of changeover that can be given to the production plan. Due to this dependency, expected benefits of SMED cannot be realized. In this paper, an application of a fuzzy inference system (FIS) is presented for parameter adjustments during changeovers on plastic injection molds. The proposed system captures the highest level of domain expertise and makes it applicable by machine operators. Integrating this system into SMED applications encourages production lot size reduction. Moreover, proposed FIS increases the quality awareness of machine operators and can be used to train new ones.

This paper shares a real industry experience for an improvement project of the changeover process through a conventional Single-Minute Exchange Die (SMED) method and other process improvement application tools. This project focuses on the changeover activities for one of the advanced composite manufacturing processes, called trimming process that involves 5-axis CNC machine operation. The cause and effect and five whys analysis techniques and some steps of conventional SMED are applied in this improvement project. Four standard strategies and priorities sequence are introduced for an extension step of conventional SMED. The conceptual decision model is then proposed to present the systematic improvement process carried out in this project. Four specific solutions from the selected strategies are then recommended to be implemented. The current implementation results show that the total changeover time is reduced to 44% and internal type activities time is reduced to 48%. The paper discusses some key success factors and future recommendations of the current project.

Changeover times can have a significant impact on the scheduling of manufacturing operations. Unfortunately, accounting for changeovers in mixed-integer programming (MIP) scheduling formulations makes the resulting models computationally more expensive. We propose five new formulations for sequence-dependent changeovers, applicable to a wide range of scheduling problems. We generate constraints for different sets of time points and sets of tasks. We also propose valid inequalities for makespan minimization. Furthermore, we prove results regarding the relative tightness of each formulation. Finally, we perform a computational study. Interestingly, we find that tighter formulations do not always lead to faster solution times, and we show that some of the new formulations perform better than the previously proposed ones.

Manufacturers are required to compete in the global marketplace, both responsively and in a sustainable manner. In order to be responsive to the customers’ dynamic needs and lower production costs, manufacturers often are required to produce a variety of products on a single production system, thereby ensuring agility and sustainability. It takes time and resources when a production system switches from one product to another, particularly in a frequent time-efficient mode. This paper aims to highlight the possible improvements in the overall capability of a production system, which remains one of the most significant facets in lowering production change over time with greater efficiency using some proposed methodologies. These include automation as well as the introduction of numerous types of conveyor in order to reduce changeover time. To that end, an industrial case study is conducted on a food production plant. To attain the objectives of maximum production and waste-reduction, a virtual production plant model is developed using Arena software by comparing existing production setups. The virtual simulation-based case study encompasses the changes in facility layout, process automation, process mapping, manufacturing complexity issues, changeover cycles as well as sustainability in the production system.

Organizations focus must reside in their constant desire for improvement in order to satisfy their clients as a result of high-quality products, thus maximizing their profits through a waste reduction in the flow production. Lean thinking allows organizations to identify and eliminate wastes within the organization. The use of lean tools is considered a simple, efficient and cost-effective solution to achieve productivity and profit. DMAIC (Define, Measure, Analyze, Improve, Control) is a problem-solving methodology that improves processes, allows defect reduction and reduction of process variability, allowing companies to continuously improve their efficiency and performance. In this work, a combined methodology iLeanDMAIC based on Lean Tools and DMAIC was developed, aiming to help organizations to easily and accurately solve their problems. It includes a case-study implementation on an organization of the sector of wood products. We were able to successfully validate this methodology and to show its efficacy in enhancing production. Results using iLeanDMAIC allowed a reduction time in changeover in the assembly machine (from 39 min to 17 min), presenting this a 44% gain on manufacture. iLeanDMAIC can help organizations thrive against their competitors, make their business more cost-effective and efficient.

It is known that the use of granular forms of fertilizers is a universal solution for plant growing enterprises using organic, mineral, organomineral fertilizers in their activities. For crop farming enterprises, the application of granular fertilizers is the most convenient way to enrich the soil with nutrients. For the surface main application and top dressing, spreaders of different designs are used, distributing fertilizers in a continuous layer with different indicators of uniformity. At present, the development of machines of various designs is underway to operate applying solid fertilizers. The main tasks of research by various authors in the field of mechanization of the distribution of fertilizers over the surface of the field are to reduce the uneven distribution of fertilizers across the width, increase the sowing width, as well as reduce the changeover time for the fertilization operation. The article presents studies related to the improvement of the design of the working bodies of the machine for applying granular fertilizers, installed on the horizontal axis of rotation. To achieve the goal of increasing the working width of the unit without reducing the quality of the sifting, an option was proposed to supplement the design of a low-frame body spreader for solid fertilizers.

This article discusses how to apply Single Minute Exchange of Die (SMED) methodology in the food industry, bearing in mind the peculiarities of this sector, as it is comprised within the mass market industry (cleaning and cosmetics products, textile, etc.). Regarding innovation, this research delves into the application of SMED to the field of machine changeovers (changes in format, products, tools, etc.), while also analysing the possible in order to be minimised. These losses are focused on irregular machine changeovers, that is, lack of standard work methodology, maintenance defects, lack of spare parts, lack of operator specialisation, etc. The implemented methodology contains a proposal to measure the results of the SMED technique using the mean time between failures (MTBF) and mean time to repair such failure (MTTR) along with indicators such as global efficiency (GE) and overall equipment effectiveness (OEE). MTBF and MTTR help evaluate and improve the implementation of SMED-based methodology. But we can also assess how long it takes us to act in the event of contingency, such as a line failure or repair, and reduce it accordingly.

This article considers the challenging problem of production lot sizing and scheduling that arises in the glass container industry. In such manufacturing environment, a furnace operates continuously feeding its attendant container forming machines with melted glass. Setups in the aforementioned machines interrupt the melted glass flow and, hence, the glass paste undergoes a heat loss. Consequently, a warm-up process is needed after each setup changeover. In addition, setups can affect the furnace output (total amount of glass extracted from the furnace) resulting in extraction variation losses. Both warm-ups and furnace extraction variations prevent the capacity of machines from being fully used and incur in additional costs. This study addresses such specificities for the first time in lot sizing and scheduling literature by introducing a novel integer programming model, which represents the problem appropriately, and a variable neighborhood search (VNS) solution method. A relevant case study conducted in an amber glass bottle plant shows that the model is able to comprise the problem requirements, and the VNS produces good-quality solutions in reasonable computational times. The reproducibility of the results is ensured by additional experiments involving artificial instances.

Soft sensors are used to predict response variables, as these variables are difficult to measure, the prediction models use data of predictors that are relatively easier to obtain. Arranging time-lagged data of predictors and applying the partial least squares (PLS) method to the dataset is a popular approach for extracting the correlation between data of the responses and predictors of the process dynamic. Because irrelevant inputs deteriorate the prediction performance of the soft sensor, the selection of variables in the PLS-based model is a critical step for developing a robust and accurate model. Furthermore, it is necessary to reselect the important predictors of a soft sensor when the operating mode is changed. However, a switch in the operating mode may not be measured, directly. In this study, two statistics are proposed to detect a change of operating mode to enable the reselection of the predictors of the soft sensor. This work involved the development of a soft sensor based on operating data from the industrial ethane removal (de-ethane) process. The changeover of crude oil types cannot be observed from the data of process variables; however, the correlation between input and output variables is significantly affected by the different types of crude oil. The result shows that the use of a soft sensor with online variable reselection is capable of maintaining the accuracy and robustness of the inferential model, effectively.

In this paper, the resource-constrained project scheduling problem with general temporal constraints is extended by the concept of break-calendars in order to incorporate the possible absence of renewable resources. Three binary linear model formulations are presented that use either start-based or changeover-based or execution-based binary decision variables. In addition, a priority-rule method as well as three different versions of a scatter search procedure are proposed in order to solve the problem heuristically. All exact and heuristic solution procedures use a new and powerful time planning method, which identifies all time- and calendar-feasible start times for activities as well as all corresponding absolute time lags between activities. In a comprehensive performance analysis, small- and medium-scale instances are solved with CPLEX 12.6. Furthermore, large-scale instances of the problem are tackled with scatter search, where the results of the three versions are compared to each other and to the priority-rule method.

The purpose of this study is an attempt to improve the functionality of a conventional Fused Deposition Modeling (FDM) process using the Automatic Tool Changer (ATC) to perform multi-material production and post-processing. Hybrid-FDM means a fusion of an Additive Manufacturing process and grinding process using the ATC system. In order to enhance the potentiality of production capacity for multi-material fabrication and surface roughness improvement, two extrusion tools and one grinding tool system are suggested. A pneumatic chuck is attached on a moving platform in the XY axes plane and an extrusion head and grinding head are placed in a docking station, allowing for a quick changeover with each other. Therefore, the manufacturing lead time can be reduced efficiently for the fabrication of a product.

The purpose of this paper is to develop a mathematical model towards minimization of total cost across echelons in a multi-product supply chain environment. The scenario under consideration is a two-echelon supply chain system with one manufacturer, one retailer and M products. The retailer faces independent Poisson demand for each product. The retailer and the manufacturer are closely coupled in the sense that the information about any depletion in the inventory of a product at a retailer’s end is immediately available to the manufacturer. Further, stock-out is backordered at the retailer’s end. Thus the costs incurred at the retailer’s end are the holding costs and the backorder costs. The manufacturer has only one processor which is time shared among the M products. Production changeover from one product to another entails a fixed setup cost and a fixed set up time. Each unit of a product has a production time. Considering the cost components, and assuming transportation time and cost to be negligible, the objective of the study is to minimize the expected total cost considering both the manufacturer and retailer. In the process two aspects are to be defined. Firstly, every time a product is taken up for production, how much of it (production batch size, q) should be produced. Considering a large value of q favors the manufacturer while a small value of q suits the retailers. Secondly, for a given batch size q, at what level of retailer’s inventory (production queuing point), the batch size S of a product be taken up for production by the manufacturer. A higher value of S incurs more holding cost whereas a lower value of S increases the chance of backorder. A tradeoff between the holding and backorder cost must be taken into consideration while choosing an optimal value of S. It may be noted that due to multiple products and single processor, a product ‘taken’ up for production may not get the processor immediately, and may have to wait in a queue. The ‘S’ should factor in the probability of waiting time in the queue.

The present paper introduces an integrated approach to support the process engineers during the implementation of the conventional Single Minute Exchange of Dies. In particular, the proposed approach grounds on the new concept of ‘duplication strategy’, and takes advantage of an implementation tool here presented. It follows a top-down functional decomposition of machines, which helps practitioners identifying all those items impacting on the changeover process, and to propose appropriate intervention strategies. It aims at verifying the possibility of replicating entire parts of machines, fixtures and/or equipment, in order to externalise as many tasks as possible, yet carefully evaluating the cost-benefit ratio and any operational issue of the intervention. To show this novel approach, an actual implementation is hereby fully described. Finally, the results of the study are commented and proposals for future possible developments are suggested.

This article seeks to establish the effectiveness of lean manufacturing in eliminating the hidden wastes, maintaining better inventory control and reducing the total production time. A large Indian foundry facility is utilised to illustrate the adopted approach. Firstly, current state mapping is prepared to have the knowledge of the existing procedure followed in the production of castings. In addition, relevant data such as, cycle time, changeover time, percentage of defects, percentage downtime and inventory in between the processes are collected for each process. Further, the future state map is created, after amending the entire process, by adopting the methodology proposed by Rother and Shook (1999). Additionally, the required buffer size (number of Kanbans) at each stage and the sequence of production are also estimated by adopting the method advocated by the Smalley (2004). Finally, improvement is accounted in terms of reduced lead time of the process.