153 research outputs found

    Bottleneck identification and analysis for an underground blast cycle operation

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    Increasing demand for raw materials and base metals together with severe environmental regulations influence mining operations to be more economic, competitive, and sustainable. Since mining involve numerous operations which difficulty ranges from simple to very complex, each of them need proper design, performance and optimization. Mining operations including activities within blasting cycle affects productivity the most, and thereby their planning and performance is the most important from production point of view. Since blasting cycle operations include many complex activities where many inner and outer factors have an influence on operating efficiency, it is crucial to thoroughly investigate the system every time new problems arise or when looking for improvements. According to Theory of Constraints every production system has at least one bottleneck. Blast cycle operations may be treated as a system regarding production. Therefore, there is/are constraint(s) which should be solved and bottleneck(s) should be debottlenecked. It is in demand to properly identify constraints within the blasting cycle operations and subsequently take measures to improve them for enhanced production results. Due to system complexity and presence of many factors and variables it is efficient to use some techniques that will facilitate analysis. Discrete event simulation approach makes it possible to analyze underground mining operations and identify critical points where improvements could be made. In these thesis computer simulation approach, together with concepts derived from theory of constraints were used to identify bottleneck and perform its analysis. Many simulations were conducted to search for improvements and indicate those with the highest potential for development and increase of production

    An agent-based simulator for quantifying the cost of uncertainty in production systems

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    Product-mix problems, where a range of products that generate different incomes compete for a limited set of production resources, are key to the success of many organisations. In their deterministic forms, these are simple optimisation problems; however, the consideration of stochasticity may turn them into analytically and/or computationally intractable problems. Thus, simulation becomes a powerful approach for providing efficient solutions to real-world productmix problems. In this paper, we develop a simulator for exploring the cost of uncertainty in these production systems using Petri nets and agent-based techniques. Specifically, we implement a stochastic version of Goldratt’s PQ problem that incorporates uncertainty in the volume and mix of customer demand. Through statistics, we derive regression models that link the net profit to the level of variability in the volume and mix. While the net profit decreases as uncertainty grows, we find that the system is able to effectively accommodate a certain level of variability when using a Drum-Buffer-Rope mechanism. In this regard, we reveal that the system is more robust to mix than to volume uncertainty. Later, we analyse the cost-benefit trade-off of uncertainty reduction, which has important implications for professionals. This analysis may help them optimise the profitability of investments. In this regard, we observe that mitigating volume uncertainty should be given higher consideration when the costs of reducing variability are low, while the efforts are best concentrated on alleviating mix uncertainty under high costs.This article was financially supported by the State Research Agency of the Spanish Ministry of Science and Innovation (MCIN/AEI/ 10.13039/50110 0 011033), via the project SPUR, with grant ref. PID2020–117021GB-I00. In addition, the authors greatly appreciate the valuable and constructive feedback received from the Editorial team of this journal and two anonymous reviewers in the different stages of the review process

    On the meaning of ConWIP cards:an assessment by simulation

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    The simplicity of Constant Work-In-Process (ConWIP) makes it one of the most widely adopted card-based production control solutions. Its simplicity, however, also limits the opportunities that are available to improve the concept. There are arguably only two major search directions: (i) to alter the meaning of cards away from controlling jobs; and (ii) to adopt alternative, more sophisticated backlog sequencing rules. In this study, we outline a simple, practical load-based ConWIP system that changes the meaning of cards. Rather than controlling the number of jobs, cards are associated with a certain amount of workload. Simulation results demonstrate the positive performance impact of limiting the total shop load. The Workload Control literature advocates the use of a corrected load measure as it better represents the direct load queuing at a station; but this worsens performance when compared to a shop load measure in the context of ConWIP

    Model Development Of A Conwip System For Production Control In Multi-Stage Multiproduct Manufacturing Environments Consisting Of High-Runner And Low-Runner Product Families

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    Production control systems can be generally categorized as push or pull systems. In a push system, production is initiated at scheduled times, whereas in a pull system, production is initiated when a signal is received. However, there are limitations to each system. Push systems are controlled by observing throughput, which requires an estimation of system capacity. Inaccurate estimates can cause work-in-process (WIP) to increase beyond the limit. Pull systems require maintaining a small amount of WIP for each product family. Nevertheless, a large product mix may still result in a high WIP level. The aim of this research is to develop and investigate a new pull system (made up of several variants) known as a parallel constant work-in-process (CONWIP) system. In the systems, product families are classified into two classes (high-runner and low-runner) based on the demand of the product mix. Each class uses a CONWIP system, where production is initiated upon withdrawal of finished goods

    Order review and release in make-to-order flow shops:analysis and design of new methods

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    Increased customization has strengthened the importance of make-to-order companies. The advent of lean management and the introduction of smart and flexible technologies has enabled many of these companies to create flow shop routings. Order review and release (ORR) research, which originally focused on job shops, has started paying attention to flow shops. However, the results have not provided clarity on the best ORR method for flow shops. This study aims at developing such a method by applying a modular design approach. It identifies the relevant elements of ORR methods for flow shops, combines them into new methods and evaluates them in a simulation study. The simulation results demonstrate that performance in pure flow shops can be strongly improved by applying the right combination of workload measures, load balancing, and order dispatching. Specifically, the results show that (1) classical workload measures are still as effective as novel measures that have been suggested for flow shops, (2) balancing workloads explicitly through optimization at the order release stage strongly improves performance, and (3) shortest processing time dispatching is highly effective in flow shops as it avoids starvation of stations. In-depth analyses have been executed to unravel the reasons of performance improvements. As such, the article provides clarity on the improvement potential that is available for ORR in flow shops, while the new modular methods provide a first step in exploiting this potential

    Dynamics of short-term operations scheduling in systematic supply chain distribution centres.

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    M. Com. University of KwaZulu-Natal, Durban, 2014.A warehouse or distribution centre has a key and vital role to play in the success of modern supply chains within business in recent times – where the term ‘warehouse’ is referred to as the commercial buildings for buffering and storing of goods. Cross docking on the other hand is more concerned with the minimisation of transportation costs within the supply chain. In as much as it is a warehouse, cross docking looks at the transit of shipment of inbound goods to their prescribed destination within a period of less than 24 hours with no intention of keeping an inventory. One of the motivating facts that drive warehouses and distribution centres into being more efficient are the customer demands to deliver the requested shipments on time, in the right quantity, in the right place with affordable price. In this study, the researcher analyses the dynamics of short-term scheduling in systematic supply chain distribution centres. The aim is to understand inbound and outbound operations, internal information sharing and to understand the role of short-term scheduling on resolving bottleneck. The phenomena of short-term scheduling is modeled by efficient scheduling of trucks, challenges encountered from inbound right through to outbound and the magnitude of information sharing within and among supply chain partners

    Application of lean scheduling and production control in non-repetitive manufacturing systems using intelligent agent decision support

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    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Lean Manufacturing (LM) is widely accepted as a world-class manufacturing paradigm, its currency and superiority are manifested in numerous recent success stories. Most lean tools including Just-in-Time (JIT) were designed for repetitive serial production systems. This resulted in a substantial stream of research which dismissed a priori the suitability of LM for non-repetitive non-serial job-shops. The extension of LM into non-repetitive production systems is opposed on the basis of the sheer complexity of applying JIT pull production control in non-repetitive systems fabricating a high variety of products. However, the application of LM in job-shops is not unexplored. Studies proposing the extension of leanness into non-repetitive production systems have promoted the modification of pull control mechanisms or reconfiguration of job-shops into cellular manufacturing systems. This thesis sought to address the shortcomings of the aforementioned approaches. The contribution of this thesis to knowledge in the field of production and operations management is threefold: Firstly, a Multi-Agent System (MAS) is designed to directly apply pull production control to a good approximation of a real-life job-shop. The scale and complexity of the developed MAS prove that the application of pull production control in non-repetitive manufacturing systems is challenging, perplex and laborious. Secondly, the thesis examines three pull production control mechanisms namely, Kanban, Base Stock and Constant Work-in-Process (CONWIP) which it enhances so as to prevent system deadlocks, an issue largely unaddressed in the relevant literature. Having successfully tested the transferability of pull production control to non-repetitive manufacturing, the third contribution of this thesis is that it uses experimental and empirical data to examine the impact of pull production control on job-shop performance. The thesis identifies issues resulting from the application of pull control in job-shops which have implications for industry practice and concludes by outlining further research that can be undertaken in this direction
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