Just In Time Production Systems: An In-depth Analysis

Categories: Technology

Overview

This paper focuses on Just In Time (JIT) single– machine-planning issue with unequal discharge times and admissible unforced machine sit out of gear time as sensible suspicions happen in the assembling situations planning to limit the aggregate weighted earliness and lateness costs. Deferral underway frameworks is a crucial thing to be focussed to balance lost deal and rain check. Consequently, JIT idea is focused on including the components required. The test of embracing this typology of distribution centre comprises of diminishing inline inventories as indicated by without a moment to spare standards and the separations secured from/to the lines amid encouraging activities.

Moreover, keeping in mind the end goal to control the stream and stock of materials, distinctive parts-nourishing approaches have been proposed.

It has been demonstrated that this decision is pivotal in light of the fact that it unequivocally influences the execution of the entirety gathering frameworks and has been looked by a few authors. In reality, under certain item/process includes, the conventional line stocking arrangement might be appropriately supplanted with more successful parts-sustaining approaches: kitting , where the collection of parts required for the gathering errands is assembled together and conveyed to the sequential construction system on pre-stacked pack holders.

Purpose of Research

The general purpose of this research was to study the importance of Just In Time(JIT) production systems.

Review of Literature

In late decades, JIT-planning issue has turned out to be critical underway frameworks.

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Lateness and earliness planning issues, supposed early/late issues, were first presented by Sidney (1977).

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Numerous papers have been contemplated in single-machine-planning models with earliness and lateness cost up until now. Valente and Alves (2005) displayed a dispatch administer and an avaricious methodology in JIT condition for single-machine-booking issue without machines sit without moving time; they enhanced the arrangements that are acquired by their heuristics. Valente et al. (2005) survived JIT single machine-booking issue with various discharge times which unforced machine sit out of gear time was not reasonable. Hoogeveen (2005) investigated JIT-booking issue and concentrated on the multicriteria planning.

Valenete and Moreira (2009) considered planning single-machine issue without machine sit out of gear time and quadratic earliness and lateness expenses and after that few dispatching heuristics introduced and thought about. Valente (2008) introduced a shaft pursuit to plan single-machine issue in JIT condition with work free punishments and no machine sit still time.

By Bakerand Scudder (1990),an perfect calendar in JIT booking frameworks is the one in which each activity finishes precisely on its appointed due date (i.e. all employments are finished in a JIT mode). Besides, they assert that this idea can be meant a booking objective in a few ways. The most widely recognized way, as we underline above, to interpret this idea to a scheduling objective is using an objective that sums the penalties due to earliness and tardiness durations. Analternative approach to make an interpretation of a similar idea to a planning objective was displayed by Lann and Mosheiov (1996), which present an alternate cost work that is identified with the quantity of right on time and late.

Hendel, Runge, and Sourd (2009) presented the related model with non-acquisition. Gurel and Selim Akturk (2008) endeavour to manage process arranging, planning and preventive support (PM) choice, all the while. The goal was to limit the aggregate fulfilment time on a CNC machine. They choose preparing times of the employments which are controllable on CNC machines. They introduced another heuristic inquiry calculation to decide all the while the handling times of the employments, their arrangement and the PM plan. Alvarez-Valdes et al. (2010) introduced two quadratic whole number programming model to tackle issue with the target of aggregate weighted earliness and lateness.

Motaghedi-Larijani et al. (2011) considered a solitary machine-booking issue with arrangement subordinate set-up time to limit the aggregate expenses of lateness and earliness of all employments and costs with respect to machine handling and support exercises in which preparing time of employments are resolved by a weakening capacity. Support exercises arranged keeping in mind the end goal to diminish handling times of occupations. They connected another half breed mimicked toughening calculation to get an ideal arrangement in a sensible run time.

Computational encounters demonstrate that the half and half calculation has the better execution conversely than that of past investigations. Khorshidian et al. (2011) examined the single-machine-planning issue with acquisition in JIT condition and proposed a GA to take care of issue. Huang (2012) considered a single-machine-booking issue with shortening work handling times. The goal was to discover a calendar that limits without a doubt the greatest delay. They demonstrated that the issue can be explained in polynomial time. Benmansour, Allaoui, and Abdelhakim (2012) examined the-single-machine booking issue for limiting the expected aggregate weighted deviations of finish times from irregular normal due date. The handling time of occupations had exponentially conveyance and normal due date was a summed-up Erlang dispersion.

Alvarez-Valdes et al. (2010) introduced two quadratic whole number programming model to take care of issue with the goal of aggregate weighted earliness and lateness. Motaghedi-Larijani et al. (2011) considered a solitary machine-planning issue with grouping subordinate set-up time to limit the aggregate expenses of lateness and earliness of all occupations and costs with respect to machine handling and support exercises in which handling time of occupations are resolved by a disintegration work. Up keep exercises arranged with a specific end goal to diminish handling times of occupations. They connected another half and half re-enacted tempering calculation to get an ideal arrangement in a sensible run time.

Computational encounters demonstrate that the half breed calculation has the better execution conversely than that of past investigations. Khorshidian et al. (2011) examined the single-machine-planning issue with acquisition in JIT condition and proposed a GA to take care of issue. Huang (2012) considered a single-machine-booking issue with shortening work handling times. The goal was to discover a timetable that limits without a doubt the most extreme delay. They demonstrated that the issue can be settled in polynomial time.

Benmansour, Allaoui, and Abdelhakim (2012) examined the-single-machine planning issue for limiting the expected aggregate weighted deviations of finish times from arbitrary basic due date. The preparing time of occupations had exponentially dissemination and normal due date was a summed up Erlang circulation. They showed that the ideal calendars were appeared to be molded. Jula and Rafiey (2012) considered the choice and booking of a few occupations on a solitary machine with grouping subordinate set-up times and entirely implemented time-window limitations on the begin times of each activity. They exhibited how to create arrange based calculations to manage the coveted work in process in an assembling situation.

The viability and strength of the proposed calculations are investigated and thought about with a comprehensive inquiry approach. Mahnam, Moslehi, and Fatemi Ghomi (2013) survived the single-machine scheduling issue with unequal discharge times and sit still embed for limiting the aggregate of most extreme earliness and lateness; They proposed two dispatching decides and meta-heuristics that are named GA and molecule swarm streamlining (PSO) are displayed to take care of the issue. Kayvanfar et al. (2013) considered the single-machine planning with controllable preparing times to limit add up to lateness and earliness. They proposed three heuristics in the little issue and two meta-heuristics in medium to expansive issue as successful nearby hunt techniques. Birgin and Ronconi (2012) tended to the single-machine-booking issue with a typical due date and non-indistinguishable prepared circumstances for each activity. The goal was to limit the weighted whole of earliness and lateness punishments of the employments.

Analytical Models and Computational Methods

Mixed Integer Programming Model

A mixed integer programming model was developed to capture the intricacies of JIT scheduling, incorporating variables such as procurement, unequal release times, and machine idle time. This model aims to provide a comprehensive framework for addressing scheduling challenges in a JIT environment.

Meta-heuristic Approaches

To address the computational complexity of the model, several meta-heuristic approaches were explored:

  • Genetic Algorithms (GA) and Particle Swarm Optimization (PSO): These methods were applied to find near-optimal solutions to the scheduling problem, demonstrating the potential of meta-heuristics in handling complex optimization problems.
  • Radical-based Algorithm (ICA): This novel approach was compared with GA and PSO, showing improved performance in terms of the Relative Percentage Deviation (RPD) metric and CPU time.

Conclusion

Because of hugeness of JIT planning for mechanical condition to beat varieties from the request giving consumer loyalty, in this examination an extensive model is produced explaining by a few parts of planning. In one hand, acquisition, unequal discharge times and unforced machine sit without moving time, and then again, JIT booking, all are driving the earth to an extremely exquisite model being exceptionally considerable for these days focused industry. As of late, processing plants are outfitted with computerization and programmed unmanned assembling machines, and instruments request for particular and unpretentious arranging.

Likewise, markets and clients request on-time conveyance by which assess and group the mechanical offices. The writing contemplated every one of the angles said above independently in JIT planning which isn't viable for the present ventures. Accordingly, our proposed issue is plainly to build up a numerical show for JIT planning for a solitary machine thinking about acquisition, unequal discharge times and unforced machine sit out of gear time, which are valid in an extensive variety of genuine modern application. Additionally, because of trouble of tackling the issue utilizing correct calculations, a half and half meta-heuristic technique is composed and tried for approval. A few developments are likewise made on the arrangement ways to deal with furnish proficient arrangements with higher quality and shorter time. Then, a few measurable tests are performed utilizing the related charts to demonstrate the logical purposes of the model.

Personal Thoughts

In this paper, we tended to limiting the aggregate weighted earliness/lateness and grouping subordinate set-up costs with appropriation, unforced machine sit out of gear time and unequal discharge time in the single-machine-booking issue. Initial, a new blended whole number programming model was displayed and techniques were created for producing the powerful arrangements of this issue. At that point three meta-heuristic methodologies to be specific GA and radical focused calculation (ICA) are utilized to take care of the issue in bigger sizes. In CSA is utilized with a specific likelihood to keep away from being caught in a neighborhood ideal, and numerous examples were connected to assess their exhibitions by RPD metric. For better execution of the calculations, their parameters were adjusted by Taguchi strategy.

Computational outcomes with 90 standard tests issue and 900 occasions have uncovered that was measurably superior to anything GA and ICA, agreeing to RPD measure and CPU time. For future research, it is beneficial to build up the issue by considering set-up times. Another heading of research will be to stretch out the calculation to a more extensive class of the proposed issue, for example, the issues with priority imperatives, learning impact et cetera. Other advancement heuristic and meta-heuristic calculations might be researched for the issue.

Updated: Feb 18, 2024
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Just In Time Production Systems: An In-depth Analysis. (2024, Feb 18). Retrieved from https://studymoose.com/document/just-in-time-production-systems-an-in-depth-analysis

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