WIP Inventory Research Articles

An integrated simulation-data envelopment analysis approach for impact of line-seru conversion

This study aims to design an innovative method to evaluate the effects of line-seru conversion in terms of various environmental and economic performance criteria. For this purpose, an integrated approach using simulation and data envelopment analysis (DEA) assisted with various performance criteria is proposed for the first time. The simulation studies involve diverse scenarios for the production of a circuit breaker on assembly lines balanced with RPW and COMSOAL heuristic algorithms, and seru production systems. The simulation results indicate a significant increase in labour effectiveness and station/yatai utilization ratios, complete removal of WIP inventories, which led to a growth in productivity up to 43.29%. The number of workers, carbon-dioxide emission, required work-space, training costs of workers and equipment cost data were incorporated in the results to evaluate the applicability and relative efficiency of the developed scenarios by use of the CCR and BCC models of DEA. The calculated scale efficiency shows that the scenarios for assembly lines balanced with COMSOAL and the seru-based scenarios were both fully effective. The seru production system scenario with 6 yatais was the most effective scenario due to reduced task times after conversion. Also, line-seru conversion proved to be advantageous despite the high training costs.

A multi-objective flexible job-shop cell scheduling problem with sequence-dependent family setup times and intercellular transportation by improved NSGA-II

With the development of Industry 4.0 and requirement of smart factory, cellular manufacturing system (CMS) has been widely concerned in recent years, which may leads to reducing production cost and wip inventory due to its flexibility production with groups. Intercellular transportation consumption, sequence-dependent setup times, and batch issue in CMS are taken into consideration simultaneously in this paper. Afterwards, a multi-objective flexible job-shop cell scheduling problem (FJSCP) optimization model is established to minimize makespan, total energy consumption, and total costs. Additionally, an improved non-dominated sorting genetic algorithm is adopted to solve the problem. Meanwhile, for improving local search ability, hybrid variable neighborhood (HVNS) is adopted in selection, crossover, and mutation operations to further improve algorithm performance. Finally, the validity of proposed algorithm is demonstrated by datasets of benchmark scheduling instances from literature. The statistical result illustrates that improved method has a better or an equivalent performance when compared with some heuristic algorithms with similar types of instances. Besides, it is also compared with one type scalarization method, the proposed algorithm exhibits better performance based on hypervolume analysis under different instances.

АВТОМАТИЗИРОВАННАЯ СИСТЕМА ОПЕРАТИВНОГО КАЛЕНДАРНОГО ПЛАНИРОВАНИЯ МНОГОСТАДИЙНОГО ПРОИЗВОДСТВА: МАТЕМАТИЧЕСКАЯ МОДЕЛЬ И ПРОГРАММНАЯ РЕАЛИЗАЦИЯ

The purpose of the study is to improve the efficiency of production areas of multi-stage production with the possibility of rational use of equipment capacity and stocks of WIP inventory in the operation conditions of the automated operational scheduling system. Features of the considered problem regarding operative calendar planning are: necessity of processing raw materials at several stages according to the flow chart; an array of the equipment which demands division of work into three periods for each party; availability of planned and unscheduled equipment downtime; necessity to complete set of orders from several suborders; availability of incomplete production in a warehouse; restrictions in order and timing of orders. In the work, the authors construct a mathematical model with the use of multidimensional matroids with structured elements in the construction of free time scale for equipment loading. The research was carried out for a metallurgical plant at the cold strip production site...

Cost value stream mapping as a lean assessment tool in a small scale industry

Value stream mapping (VSM) is a lean tool which addresses the non-value added activities in time domain. But, it fails to address it in a cost domain. In this work, a new tool called cost value stream map (CVSM) is proposed, which addresses the problems encountered in conventional VSM and cost-time profile (CTP) and maintaining the advantages of both. The determination of work in process inventory and non-value added costs incurred by using CVSM are demonstrated by presenting a case study. An SME in Kerala, India is selected for this. Lean techniques applied on the various non-value added activities in the order of their cost investments 27% reduction in lead time, 27%-32% reduction in WIP inventory and 40%-42% reduction in cost investment while manufacturing the product. The reductions when accounted annually there is a saving of INR.2,17,728 in the value added cost.

Measuring performance

Most organizations today have a set of key performance indicators (KPIs) that are used for decision-making. Because a balanced scorecard approach has been widely adopted, typically KPIs have moved beyond the basic financial metrics. However, developing the right set of KPIs is an important step in promoting continuous improvement and overall business success. Organization that implement six sigma or lean six sigma have a built-in set of KPIs, such as defects, ppm defective, process yields, process cycle times, and a variety of inventory statistics, such as WIP inventory. But I don't think this goes far enough in most situations. KPIs should be traceable to customer satisfaction, both for external customers and internal ones. Organizations should formalize customer requirements and then evaluate how they are doing with respect to this list when they conduct strategic planning sessions. This is a good way to develop the right KPIs. However, overemphasis on short-term financial results can skew this process. Too much focus on quarterly growth in sales or revenue and deflect attention from the issues that contribute to long-term business growth and success. Organizations often gravitate towards collecting data that is easy to obtain, but may not be necessarily useful. An example is information about customer satisfaction data. Surveys can be useful, but may not tell the complete story. One organization that I am familiar with has a customer service line. They reported very few serious complaints from that source. Analysis revealed that the average waiting time for customers that used this line was in excess of 30 minutes. Furthermore, the ability of the system to place calls on hold was limited, so a significant number of calls were “blocked”; that is, they were not answered at all. So the volume of customer issues that this service was designed to serve was dramatically underestimated. Some KPIs are lagging indicators of business performance. Examples include sales volumes and maintenance expenses. These are usually easy to generate, but may not provide much indication of future success. Reliable forecasts of future demand (demand isn't necessarily the same as sales) is usually a better business indicator. Leading indicators are harder to devise, almost always depend on the specific nature of the individual organization, and may be difficult to generate. For example, cycle time for new product introduction is often a critical measure of future business success in many industries. If this KPI is unsatisfactory or is getting longer for unexplained reasons it may indicate an area for lean six sigma intervention. Performance measurement is an important management tool for evaluating and improving organizational success. Leading KPIs can be an effective “canary in the coal mine” warning of impending trouble. The investment required to develop and maintain the correct set of KPIs will pay many dividends.

Work-in-Progress Inventory Control Case Study in Lean Management

Increasing the rate of converting raw material into finished product and delivering it on time is a main driver for each manufacturing industry to achieve continuous improvement in its business operation. This case study demonstrates the improvement of the work-in-progress inventory in a non-lean company seeking to adopt lean management. Introducing the value stream mapping (VSM) lean technique to identify the waste in the current production operation. A selection of lean tools such as Kanban card, supermarket racking and one-piece flow are applied to control and monitor the WIP inventory after justification of the factors (process cycle time, production facilities layout and facilities capacity allocation) that influence the change from the current production operation situation.The construction of the current VSM had identified the major waste in WIP inventory handling in the final fabrication process. The fluctuation of WIP inventory has been resolved by the implementation of supermarket racking; therefore, an improvement base for WIP inventory control has been established. Throughout this study, the lean management concept had been fostered into the production floor team and will continue developing to the organization.

Response surface approach to robust design of assembly cells through simulation

PurposeThis paper aims to present a multi-response robust design (RD) optimization approach for U-shaped assembly cells (ACs) with multi-functional walking-workers by using operational design (OD) factors in a simulation setting. The proposed methodology incorporated the design factors related to the operation of ACs into an RD framework. Utilization of OD factors provided a practical design approach for ACs addressing system robustness without modifying the cell structure.Design/methodology/approachTaguchi’s design philosophy and response surface meta-models have been combined for robust simulation optimization (SO). Multiple performance measures have been considered for the study and concurrently optimized by using a multi-response optimization (MRO) approach. Simulation setting provided flexibility in experimental design selection and facilitated experiments by avoiding cost and time constraints in real-world experiments.FindingsThe present approach is illustrated through RD of an AC for performance measures: average throughput time, average WIP inventory and cycle time. Findings are in line with expectations that a significant reduction in performance variability is attainable by trading-off optimality for robustness. Reductions in expected performance (optimality) values are negligible in comparison to reductions in performance variability (robustness).Practical implicationsACs designed for robustness are more likely to meet design objectives once they are implemented, preventing changes or roll-backs. Successful implementations serve as examples to shop-floor personnel alleviating issues such as operator/supervisor resistance and scepticism, encouraging participation and facilitating teamwork.Originality/valueACs include many activities related to cell operation which can be used for performance optimization. The proposed framework is a realistic design approach using OD factors and considering system stochasticity in terms of noise factors for RD optimization through simulation. To the best of the authors’ knowledge, it is the first time a multi-response RD optimization approach for U-shaped manual ACs with multi-functional walking-workers using factors related to AC operation is proposed.

Assessment of CIM implementation in SMEs: a multiple case study approach

Considering the contribution of small and medium enterprises to the national economic development, employment opportunities generation and total manufacturing output, their role cannot be overemphasized. SMEs have more ability to innovate and flexibility as compared to large organizations irrespective of their size as well as organizational structure. Therefore, it is important to improve their competitiveness and performance. This may be done by the implementation of computer-integrated manufacturing (CIM), because it plays a vital role in SMEs from all aspects of competitiveness both in terms of products and production techniques. An effort has been made in this paper to develop a model by considering four parameters such as top-management support and strategic alliance, business structure, structural attributes and integration of systems. Furthermore, multiple case studies have been conducted in British SMEs to explore the potential of CIM with the help of the proposed model. The result shows that there is lack of long-term strategic vision of the top management in HHW company. Whereas, a survey of SMEs have pointed out increase in reliability of delivery date, throughput/production volume, level of product customisation, reduction in manufacturing costs, WIP inventory and improvement in the image of the companies with the implementation of CIM.

A metamodel-based Monte Carlo simulation approach for responsive production planning of manufacturing systems

Production planning is concerned with finding a release plan of jobs into a manufacturing system so that its actual outputs over time match the customer demand with the least cost. For a given release plan, the system outputs, work in process inventory (WIP) levels and job completions, are non-stationary bivariate time series that interact with time series representing customer demand, resulting in the fulfillment/non-fulfillment of demand and the holding cost of both WIP and finished-goods inventory. The relationship between a release plan and its resulting performance metrics (typically, mean/variance of the total cost and the fill rate) has proven difficult to quantify. This work develops a metamodel-based Monte Carlo simulation (MCS) method to accurately capture the dynamic, stochastic behavior of a manufacturing system, and to allow real-time evaluation of a release plan's performance metrics. This evaluation capability is then embedded in a multi-objective optimization framework to search for near-optimal release plans. The proposed method has been applied to a scaled-down semiconductor fabrication system to demonstrate the quality of the metamodel-based MCS evaluation and the results of plan optimization.

A comparison of HK-CONWIP and BK-CONWIP control strategies in a multi-product manufacturing system

This paper evaluates the performance of the Hybrid Kanban Constant Work-In-Process control strategy and Basestock Kanban Constant Work-In-Process control strategy operating Shared Kanban Allocation Policy (S-KAP) and Dedicated Kanban Allocation Policy (D-KAP) in a multi-product serial flow line. We explored the effect of an increase of product types on the WIP inventory in the system. A simulation-based optimisation technique was used in determining the optimal settings for the strategies. The strategies were compared via pairwise comparison technique and Nelson’s ranking and selection procedure. S-KAP responds quicker to demand than D-KAP. BK-CONWIP outperforms HK-CONWIP in a serial manufacturing system. It was shown that an increase in the number of product-type increases the number of PAC and WIP inventory.

Rough cut capacity planning-(RCCP)-(case study)

Many people are familiar with the Manufacturing Planning and Control (MPC) Systems which are driven by Material requirements planning (MRP) engines. In such systems MRP uses a master production schedule (MPS) of end items to determine the quantity and timing of component parts’ production. MRP does not consider any capacity limitation; it strictly assumes that, sufficient capacity is available to produce components at the time when they are needed. The most common problem which is encountered in operating MRP based systems is the existence of an overstated MPS. An overstated master production schedule is the one which orders more than the production resources can complete. An overstated MPS causes raw materials and WIP inventories to increase because more materials are purchased and released to the shop than are completed and shipped. It also causes a buildup of queues on the shop floor. Since jobs have to wait to be processed, actual lead times increase, causing ship dates to be missed. As lead times increase, forecast over the planning horizon becomes less accurate. This is because of the fact that, forecasts are more accurate for shorter periods than for longer ones. Thus, overstated master production schedules lead to missed due dates. Because of all the above given reasons, validating the MPS with respect to available capacity is an extremely important step in MRP. The term used for this validation exercise is “Rough Cut Capacity Planning (RCCP)”. The methods commonly used in energy planning outline is a technique factors College ((Overall Factors, and is a way to convert the amount of products contained in the scheduling main production to the power requirements are expressed in hours of work a total of some or all production resources (processes or certain sections). Then these requirements are being distributed from the total energy required to types of energy depending on the rates of use of each type to

Single-item production–delivery scheduling problem with stage-dependent inventory costs and due-date considerations

This paper studies an integrated scheduling problem for a single-item, make-to-order supply chain system consisting of one supplier, one capacitated transporter and one customer. Specifically, we assume the existence in the production stage of an intermediate inventory that works as a buffer to balance the production rate and the transportation speed. Jobs are first processed on a single machine in the production stage, and then delivered to the pre-specified customer by a capacitated vehicle in the delivery stage. Each job has a due date specified by the customer, and must be delivered to the customer before its due date. Moreover, it is assumed that a job that is finished before its departure date or arrives at the customer before its due date will incur a stage-dependent corresponding inventory cost (WIP inventory, finished-good inventory or customer inventory cost). The objective is to find a coordinated production and delivery schedule such that the sum of setup, delivery and inventory costs is minimised. We formulate the problem as a nonlinear model in a general way and provide some properties. We then derive a precise instance from the general model and develop a heuristic algorithm for solving this precise instance. In order to evaluate the performance of the heuristic algorithm, we propose a simple branch-and-bound (B&B) approach for small-size problems, and a lower bound based on the Lagrangian relaxation method for large-size problems. Computational experiments show that the heuristic algorithm performs well on randomly generated problems.

Seru

The Toyota production system (TPS) or lean has long been regarded as a powerful approach for managing manufacturing factories. However, in the early 1990s, the TPS was found not to work when it was applied to Japanese electronics companies. TPS is fit for a stable, but not volatile, business environment such as that which the electronics industry belongs. This volatile environment can be described as one with short product life cycles, uncertain product types, and fluctuating production volumes (sometimes mass, sometimes batch, and sometimes very small volumes). Seru, a new production organization, was developed to cope with this environment. Many leading global companies such as Samsung, Sony, Canon, Panasonic, LG, and Fujitsu have adopted seru. Seru overcame a lot of disadvantages inherent in TPS and brought amazing benefits to seru users. For example: 1) Seru requires a much smaller workforce, 2) It can greatly reduce space requirements, and 3) It can reduce lead time, setup time, WIP inventories, finished-product inventories, and cost. This article introduces seru’s history and defines various seru types. A seru pyramid is constructed to compare seru with the TPS. A JIT organization system is introduced. The authors show why applying it can bring great productivity, efficiency, and flexibility to a production organization.

Improvement of manufacturing operations at a pharmaceutical company

Purpose – The current good manufacturing practices (cGMP) are followed in the pharmaceutical sector to ensure that products are consistently produced and controlled to the appropriate quality standards as required by the marketing agencies. The purpose of this paper is to share improvement experiences due to implementation of lean principles combined with cGMP in a pharmaceutical company.Design/methodology/approach – To conduct the study, an intensive review of literature has been conducted. For analysis of the problems existing in the selected production line, the 5‐whys methodology was followed. The current state value stream map (VSM) has been developed after making several company visits and necessary computations. For improvement of the system, various lean strategies have been proposed and the future state VSM developed.Findings – The methodology assisted this company in reducing lead times, cycle times and WIP inventory in the manufacturing process. Furthermore, the storage area was reduced by 38 p...

Application of Flexible Lean Tools for Restructuring of Manufacturing Operations: A Case Study

The purpose of this paper is to provide an insight on the application of flexible lean tools to a local company for restructuring of the manufacturing operations. The study assists managers in the documentation of the value streams, to strive continuously for perfection and to ensure flexibility in restructuring of their manufacturing operations. To conduct the study, both qualitative and quantitative approaches were followed. In documenting value stream map (VSM), a focus group of employees from production, logistics and warehouse departments was involved. The relevant data was collected through interviews and field visits. For improvement of the system, lean tools such as 5S, one-piece flow and electronic information system (eIs) have been proposed. The lean implementation in the selected manufacturing company yielded waste reduction due to inappropriate processing (39%), reduction in final inventory (70%), reduction in floor area (45%), reduction in manpower (50%), reduction in cycle time (48%), reduction in WIP inventory (83%), and reduction in non-value added time (60%). The flexible lean tools recommended in this research can support practitioners in improving both production efficiency and flexibility in restructuring of manufacturing operations.

Coordinated scheduling of production and delivery stages with stage-dependent inventory holding costs

This paper considers a problem of integrated decision-making for job scheduling and delivery batching wherein different inventory holding costs between production and delivery stages are allowed. In the problem, jobs are processed on a facility at a production stage and then delivered at the subsequent delivery stage by a capacitated vehicle. The objective is to find the coordinated schedule of production and delivery that minimizes the total cost of the associated WIP inventory, finished product inventory and delivery, where both the inventory costs are characterized in terms of the weighted flow-time and the delivery cost is proportional to the required number of delivery batches. It is proved that the problem is NP-hard in the strong sense. Thereupon, three heuristic algorithms are derived. Some restricted cases are also characterized as being solvable in polynomial time. Numerical experiments are conducted to evaluate the performance of the derived heuristic algorithms.

Impact of Production Control and System Factors in Semiconductor Wafer Fabrication

This paper validates a proposed job release methodology and experimentally investigates the impact of production control methodologies and system factors on wafer fab performance in terms of average cycle time, standard deviation of cycle time, average lateness, WIP inventory and fab output by simulating a wafer fab of Chartered Semiconductor Manufacturing Ltd (Chartered) and statistically analyzing the experimental results using t-test and ANOVA. A full factorial design of experiment is conducted to evaluate the performance of three job release methodologies, three dispatching rules and three greedy levels of batching policy under different system environmental settings differentiated by fab output level and machine unreliability level. Based on the experimental results, the proposed job release methodology WIPLOAD control (WIPLCtrl) appears to be very efficient to be able to potentially improve all the considered performance measures simultaneously. The advantage of WIPLCtrl is robust to the change of system environmental conditions. In contrast, the improvement brought by a dispatching rule on a certain performance measure might cost the deterioration of other performances. Considering the relative impact on the fab performance, job release control appears to be the most important production control factor in comparison with dispatching and batching policy, especially when the system is operating on a high output level and/or with a high system variability level caused by machine unreliability.

Zone design and control for vehicle collision prevention and load balancing in a zone control AGV system

Because of their routing flexibility, automated guided vehicles (AGVs) have been used in many manufacturing systems, especially those in which parts with diverse and complex processing routes are made. In recent years, there have been many studies on AGV-related problems. One of them is preventing the collision of vehicles. Some traditional vehicle collision prevention strategies are zone strategies that divide guide paths into several non-overlapping zones and restrict the presence of only one vehicle in any zone at any time. Traditional zone strategies are fixed zone strategies in which the area of a zone is fixed and vehicles are not allowed to help each other. Because of these restrictions, fixed zone strategies cannot always satisfy the system’s transportation demand if there is a load imbalance between vehicles of different zones. In this paper, a new zone strategy is proposed for a zone control AGV system with a network guide path. The proposed strategy is a dynamic zone strategy, which is different from a fixed zone strategy. It relies on two methods – zone partition design and dynamic zone control – to prevent the collision of vehicles and to maintain the load balance between the vehicles of different zones. The zone partition design defines a relationship coefficient, which measures both the distance relationship and the flow relationship between workstations, and uses it to find an initial zone partition design. We then improve this initial design by an SA (Simulated Annealing) based improvement procedure to achieve a better load balance result. The dynamic zone control uses two methods – zone repartition and load sharing – to ensure that vehicle collision can be prevented and the system’s load balance can be maintained when the system is in operation. Simulation experiments were conducted to understand the performance of the proposed strategy. The simulation results show that the proposed strategy outperform the fixed zone strategy in throughput, WIP inventory, and flow time. The results also show that the proposed strategy is able to adapt to any changes (in the system) that cause the load imbalance problem between zones.

3716 多目的最適化手法による生産ラインの製品投入順序づけ(S66-2 生産システムの新展開(基礎理論)(2),S66 生産システムの新展開(基礎理論))

Mixed-model assembly line is a typical production process to cope with diversified customer demands effectively and practically. Since it produces various products on the same assembly line, a rational management is of special importance. From this aspect, this study focuses on a sequencing problem of mixed-model assembly line including paint line as its preceding process. In order to keep production balance at a mixed-model assembly line and a painting line, we formulate the sequencing problem as a multi-objective optimization problem under three objectives, i.e., leveling the workload, smoothing the part usage, and reducing the WIP inventory. Moreover, we proposed a practical method for solving the resulting problem by the aid of meta-heuristic method like SA and the multi-objective optimization method known as MOON^<2R>. Through numerical experiments, we verify the validity of the proposed approach.

Matching plant flexibility and supplier flexibility: Lessons from small suppliers of U.S. manufacturing plants in India

This is a study about the flexibility of manufacturers and their small suppliers; a subject of growing interest today (Swafford, P.M., Ghosh, S., Murthy, N., 2006. The antecedents of supply chain agility of a firm: Scale development and model testing, Journal of Operations Management 24 (2), 170–188.) The study is based on empirical data collected from U.S. manufacturing plants operating in India and their small suppliers. While globalization is causing hundreds of multinational firms from developed countries to locate manufacturing facilities in developing countries such as China and India, the supply chain environment in China and India is different from domestic supply chains environments familiar to U.S. manufacturers venturing to such countries. For global ventures of multinationals to succeed, multinational firms must strive to understand the supply environment and practices in countries such as China and India. The literature on supply chain has two shortcomings. First, studies have not investigated the result of matched plant and supplier flexibility. Second, although, supply chain in the U.S. has been investigated by numerous researchers, the same is not true about the supply chains in developing countries such as China and India. This paper strives to fill these two voids. A survey of U.S. manufacturing plants in given SIC classifications found that U.S. plants preferred the following: (1) stable JIT suppliers and (2) proximate flexible suppliers. An Additional finding was that suppliers were engaged in: (1) JIT material supply and (2) automated material supply. Our regression model explains up to 38% of the variance in profitability (power = 0.7). A notable finding about fit is that profitability is highest when an inflexible plant uses small inflexible suppliers. Profitability is above average when a flexible plant uses flexible small suppliers. In contrast, if there is a mismatch of plant flexibility with supplier flexibility, the profitability is below average. The regression model for WIP inventory explains over 44% of the variance (power = 0.9). Lower levels of WIP inventory were associated with JIT practices of small suppliers. The mismatch between factory and supplier flexibility is associated with lower WIP inventory, a finding that deserves further investigation. This study demonstrates one practical method of studying the fit between a factory and its suppliers. Methodological contributions of this paper are twofold. First, it demonstrates how to select and use appropriate research tools to conduct scientific studies using borderline samples. This is a useful contribution to the OM area when OM empirical research is routinely shying away from borderline samples. Second, interaction effects are investigated at great depth using methods not seen in OM literature.