Aggregate planning and forecasting in make-to-order production systems

Gansterer, Margaretha

doi:10.1016/j.ijpe.2015.06.001

Cited by 63 publications

(37 citation statements)

References 46 publications

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“…Metode penjadwalan produksi induk (MPS) merupakan dasar pertimbangan untuk memastikan jumlah produk dapat memenuhi permintaan pelanggan dan penjadwalan produksi induk (MPS) memiliki peranan yang sangat penting dalam pencapaian tujuan perusahaan (Jonsson and Ivert, 2015) (Gamsterer, 2015). Jadwal produksi induk (Master Production Schedule = MPS) adalah suatu jadwal produksi untuk setiap jenis atau setiap macam barang yang didasarkan pada rencana produksi semesta yang sudah disusun untuk barang tersebut.…”

Section: Pendahuluanunclassified

Penjadwalan Produksi Iks-Filler Pada Proses Ground Calcium Carbonate Menggunakan Metode MPS Di Perusahaan Kertas

Supriyadi

Riskiyadi

2016

Sinergi

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Abstrak --Persaingan industri kertas semakin ketat dengan banyaknya industri atau perusahaan yang bergerak dalam industri yang sama dalam bersaing mendapatkan dan mempertahankan pelanggan. Permasalahan yang terjadi saat ini di CaCO3 Section pada Perusahaan Kertas adalah belum tersedianya jadwal induk produksi (Master Production PENDAHULUANIndustri di Indonesia berkembang dengan pesat menimbulkan persaingan diantara industri manufaktur untuk mencapai keuntungan yang maksimal dan menggunakan sumber daya yang efektif. industri manufaktur dihadapkan pada berbagai masalah keterbatasan faktor-faktor produksi seperti material, kapasitas mesin, metode yang digunakan dalam proses produksi, modal, dan sumber daya manusia. Sehingga semua faktor produksi tersebut harus dikelola dengan manajemen yang baik.Faktor-faktor produksi dalam industri manufaktur perlu memperhitungkan kapasitas produksi yang paling optimal agar tidak kekurangan maupun kelebihan persediaan barang yang diproduksi. Metode penjadwalan produksi induk (MPS) merupakan dasar pertimbangan untuk memastikan jumlah produk dapat memenuhi permintaan pelanggan dan penjadwalan produksi induk (MPS) memiliki peranan yang sangat penting dalam pencapaian tujuan perusahaan (Jonsson and Ivert, 2015) (Gamsterer, 2015).

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Section: Pendahuluanunclassified

Penjadwalan Produksi Iks-Filler Pada Proses Ground Calcium Carbonate Menggunakan Metode MPS Di Perusahaan Kertas

Supriyadi

Riskiyadi

2016

Sinergi

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“…In this paper, a classical APP such as presented in Gansterer (2015), is extended by an additional decision on planned utilization (see also Felberbauer and Altendorfer 2014). Table 1 shows all variables used in the MILP problem.…”

Section: Details On App Problem Studiedmentioning

confidence: 99%

“…Hierarchical production planning (HPP) models with decision levels differing in time horizon and decision variables are widely used (Hax and Meal 1975;Meal 1984;Schneeweiss 2003;Hopp and Spearman 2008), and its application has been proven to be very beneficial (Andersson, Axsäter, and Jönsson 1981;Gansterer 2015). The top-down approach of HPP causes that upper level decisions restrict the lower level decisions.…”

Section: Introductionmentioning

confidence: 99%

“…A recent study of Gansterer (2015) is a first step to close this research gap. Nevertheless, the main focus of Gansterer (2015) lies on the investigation of different forecasting techniques and neglects the discussion on how the deterministic APP model incorporates the stochastic nature of forecasts and demand which is addressed in the current study. This paper extends available literature by explicitly focusing on the effects of forecast error and demand uncertainty within a hierarchical production planning structure when applying a planned utilization factor in the APP.…”

Section: Introductionmentioning

confidence: 99%

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Effects of forecast errors on optimal utilisation in aggregate production planning with stochastic customer demand

Altendorfer

Felberbauer

Jodlbauer

2016

International Journal of Production Research

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The hierarchical structure of production planning has the advantage of assigning different decision variables to their respective time horizons and therefore ensures their manageability. However, the restrictive structure of this top-down approach implying that upper level decisions are the constraints for lower level decisions also has its shortcomings. One problem that occurs is that deterministic mixed integer decision problems are often used for long term planning but the real production system faces a set of stochastic influences. Therefore, a planned utilization factor has to be included into this deterministic aggregate planning problem. In practise this decision is often based on past data and not consciously taken. In this paper the effect of long term forecast error on the optimal planned utilization factor is evaluated for a production system facing stochastic demand and the benefit of exploiting this decision's potential is discussed. Overall costs including capacity, backorder and inventory costs, are determined with simulation for different multi-stage and multi-item production system structures. The results show that the planned utilization factor used in the aggregate planning problem has a high influence on optimal costs. Additionally, the negative effect of forecast errors is evaluated and discussed in detail for different production system environments.

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“…Models that have been used to solve the APP problem include: linear decision rule (for long-term strategic APP decisions), transportation model, dynamic programming, lot sizing model, linear programming (the most widely accepted method like in ( [11]), , heuristics [12], simulation [13], goal programming [14], micro spreadsheet analysis [15], multi-objective optimization [16], fuzzy formulation models [17,18], genetic algorithms (GAs) [19], and multiple criteria mixed integer programming [20]. Based on Holt et al, in [2], in the area of models for planning/scheduling production-inventory systems, two types of models can be identified:…”

Section: Decision Science Approaches To the Aggregate Planning Problemmentioning

confidence: 99%

Optimal Control Approaches to the Aggregate Production Planning Problem

Davizón¹,

Martínez-Olvera

Soto

et al. 2015

Sustainability

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Abstract:In the area of production planning and control, the aggregate production planning (APP) problem represents a great challenge for decision makers in production-inventory systems. Tradeoff between inventory-capacity is known as the APP problem. To address it, static and dynamic models have been proposed, which in general have several shortcomings. It is the premise of this paper that the main drawback of these proposals is, that they do not take into account the dynamic nature of the APP. For this reason, we propose the use of an Optimal Control (OC) formulation via the approach of energy-based and Hamiltonian-present value. The main contribution of this paper is the mathematical model which integrates a second order dynamical system coupled with a first order system, incorporating production rate, inventory level, and capacity as well with the associated cost by work force in the same formulation. Also, a novel result in relation with the Hamiltonian-present value in the OC formulation is that it reduces the inventory level compared with the pure energy based approach for APP. A set of simulations are provided which verifies the theoretical contribution of this work.

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Aggregate planning and forecasting in make-to-order production systems

Cited by 63 publications

References 46 publications

Penjadwalan Produksi Iks-Filler Pada Proses Ground Calcium Carbonate Menggunakan Metode MPS Di Perusahaan Kertas

Penjadwalan Produksi Iks-Filler Pada Proses Ground Calcium Carbonate Menggunakan Metode MPS Di Perusahaan Kertas

Effects of forecast errors on optimal utilisation in aggregate production planning with stochastic customer demand

Optimal Control Approaches to the Aggregate Production Planning Problem

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