Analysis of lot-sizing methods’ suitability for different manufacturing application scenarios oriented to MRP and JIT/Kanban environments

Florim, Wilson; Dias, Paulo Sousa; Santos, Alex José Souza dos; Varela, Leonilde; Madureira, Ana; Putnik, Goran D.

doi:10.14488/bjopm.2019.v16.n4.a9

Cited by 3 publications

(3 citation statements)

References 41 publications

(40 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This classification enables the researchers to focus on a certain class of the problem. The performance of one type may not be same for another as shown by Florim et al (2019).…”

Section: Literature Reviewmentioning

confidence: 98%

Evaluation of the Production Planning Policy Alternatives in a Pet Resin Production Plant: a Case Study From Turkey

Demirkan

Durmuşoğlu²

2020

BJO&PM

View full text Add to dashboard Cite

Goal: The main purpose of this work is to develop several production planning models for one of bottle grade PET production plants (in Turkey) under different scenarios by considering different levels of inventory (no stock and different levels of safety stocks), different energy sourcing alternatives (natural gas/coal or both) and production throughput (different lot sizes). Design/Methodology/Approach: Deterministic multi-product multi-period single level mixed integer linear programming model is presented. The model is implemented for the above defined scenarios. We have also considered the total emission produced for different energy alternatives. Results: The models for the different scenarios have shown that significant performance improvements can be achieved by changing the parameters/policies of the production. The best model obtained has yielded 6.6% of profit improvement and 6.9% of cost reduction. Limitations of the investigation: Planning horizon of this work could cover the data of years 2014 to 2018. However, the actual data employed for this study is limited with one year due to unavailability of further data. In addition to this, improvement of current production planning approach of the plant by implementation of proposed model is one of the objectives of this study to see success rate of model. Though, this couldn’t be realized. We hypothetically tested the improvement provided by the proposed model, therefore we can’t analyze the actual improvement. Practical implications: Interactions among optimal results obtained by running model with different scenarios and their effect on selected performance variables are the main contribution of this work. Similar methodology could be used at other PET resin manufacturing plants or alternatively the production facilities having similar type of continuous manufacturing processes to find their optimal levels of inventory, production throughput and proper choice for energy sourcing alternative. Originality/Value: The research on the production planning for PET resin industry by considering the different scenarios (levels of inventory / energy sourcing alternatives/ production throughput) is novel as far as we know, and therefore the approach used in this study is expected to be useful for other similar plants.

show abstract

“…This classification enables the researchers to focus on a certain class of the problem. The performance of one type may not be same for another as shown by Florim et al (2019).…”

Section: Literature Reviewmentioning

confidence: 98%

Evaluation of the Production Planning Policy Alternatives in a Pet Resin Production Plant: a Case Study From Turkey

Demirkan

Durmuşoğlu²

2020

BJO&PM

View full text Add to dashboard Cite

show abstract

“…In production planning, making the proper decisions about the lot size is extremely important because it directly affects the system performance and productivity [7] and this is often key for any manufacturing firm that desires to compete on market. As this is often complex moreover as important, it's been highly studied although, there's still a niche about showing the contributions to clarify the suitability of these methods used concerning each quite underlying manufacturing environment (regarding variations in demand and peaks of seasonality) [28]. Therefore this study aimed toward the…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Manufacturing Lot Size Under Stochastic Demand

S.¹

2022

ijcsrr

View full text Add to dashboard Cite

In many manufacturing problems, multi-objective optimizations are representative models, as objectives are considered a conflict with one another. In real-life applications, optimizing a specific solution concerning one objective may end up in unacceptable results concerning the other objectives. Many Manufacturing companies operate under uncertainties and this affects the system performance. Stochastic product demand is one of the challenges faced by manufacturing companies and often affects the manufacturing system’s performance and decision-making. Making the proper decisions regarding manufacturing lot-sizing problems is critical for any manufacturer because it makes the firm compete within the market. In this paper, Markov chains in conjunction with stochastic goal programming were used to develop an optimization model for the manufacturing lot size. The over-achievement or under-achievement of the manufacturing lot size was determined by defining the goal constraints, deviation variables, priorities, and objective function. The different states of demand for the product with stochastic demand were represented by states of a Markov chain. Using the applied mathematics solver in MATLAB TM, the optimization model was then solved, determining the quantity of product to be manufactured in a given quarter of the year as demand changes from one state to another.

show abstract

“…Menurut [2] dalam metode Min-Max, tingkatan kuantitas maksimum dan minimum untuk tiap jenis bahan baku sudah ditentukan. Tingkatan Minimum [3]adalah marjin pengaman yang diperlukan untuk mencegah terjadinya kekurangan bahan baku. Oleh karena itu, untuk mengatasi hal tersebut perusahaan perlu meminimalkan total biaya pemesanan persediaan bahan baku agar proses produksi dapat berjalan dengan lancar.…”

unclassified

Analisis Penerapan Metode Silver Meal Dan Min Max Dalam Pengendalian Persediaan Bahan Baku Yang Ekonomis

Suseno

Siswoko

2022

JDPT

View full text Add to dashboard Cite

Abstrak:Perumda Air Minum Tirta Binangun Kabupaten Kulon Progo merupakan alih status dari BPAM yang bergerak dibidang pelayanan air pipa dan air minum kemasan bagi masyarakat. Pada tanggal 15 Oktober 2013 Gubernur DIY meresmikan merk AirKU yaitu produk AMDK. Penelitian yang dilakukan adalah menghitung efisiensi biaya pemesanan bahan baku pendukung yaitu kardus 240 ml dengan metode Silver Meal dan untuk mengetahui dua tingkatan maksimum dan tingkatan minimum stok pemesanan kembali yang harus dilakukan dengan menggunakan metode Min Max. Masalah yang pernah dihadapi pada pabrik AirKU adalah bagaimana cara pengendalian stok agar tidak habis atau menumpuk dan meminimalkan biaya pemesanan kembali (reorder stock) agar proses produksi dapat berjalan dengan lancer dan maksimal supaya dapat mengefisiensikan total biaya pemesanan kembali (reorder stock). Dengan adanya masalah tersebut maka dilakukan penelitian efisiensi biaya reorder bahan baku kardus 240 ml dengan harapan pabrik AMDK AirKU dapat melakukan pengoptimalan reorder guna mngefisiensikan biayanya. Hasil penelitian dengan menggunakan metode Silver Meal adalah Rp 287.544.000 dan sedangkan tingkat pemesanan kembali dengan metode Min Max 9.373 pcs degan harga Rp 31.868.200 dan frekuensi reorder 1 bulan sekali, kemudian didapat efisiensinya adalah sebesar 0,258%.Kata Kunci: Silver Meal, Min Max, Persediaan bahan baku, Biaya Pemesanan, Biaya Penyimpanan.Abstract:Perumda Air Minum Tirta Binangun Kulon Progo Regency is a status transfer from BPAM which is engaged in piped water and bottled drinking water services for the community. On October 15, 2013 the Governor of DIY inaugurated the AirKU brand, namely the product AMDK PDAM Kulon Progo. The research conducted is to calculate the cost efficiency of ordering supporting raw materials, namely 240 ml cardboard with the Silver Meal method and to find out the two maximum levels and the minimum level of reordering stock that must be done using the Min Max method. The problem that has been faced at the AirKU factory is how to control stock so that it does not run out or accumulate and minimize reorder costs (reorder stock) so that the production process can run smoothly and maximally in order to streamline the total cost of reordering (reorder stock). With this problem, a research on the cost efficiency of reordering 240 ml cardboard raw materials was carried out in the hope that the AirKU AMDK factory could optimize reorders in order to streamline costs. The results of the study using the Silver Meal method were Rp. 287,544,000 and while the rate of reordering with the Min Max method was 9,373 pcs at a price of Rp. 31,868,200 and the frequency of reordering was once a month, then the efficiency was 0.258%.Keywords: Silver Meal, Min Max, Raw material inventory, Ordering cost, Storage cost

show abstract

Analysis of lot-sizing methods’ suitability for different manufacturing application scenarios oriented to MRP and JIT/Kanban environments

Cited by 3 publications

References 41 publications

Evaluation of the Production Planning Policy Alternatives in a Pet Resin Production Plant: a Case Study From Turkey

Evaluation of the Production Planning Policy Alternatives in a Pet Resin Production Plant: a Case Study From Turkey

Multi-Objective Optimization of Manufacturing Lot Size Under Stochastic Demand

Analisis Penerapan Metode Silver Meal Dan Min Max Dalam Pengendalian Persediaan Bahan Baku Yang Ekonomis

Contact Info

Product

Resources

About