Production planning decision of a dairy under supply disruption and demand uncertainty

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dayanidhi Jena ◽  
Pritee Ray
Keyword(s):  
Production Planning ◽  
Demand Uncertainty ◽  
Expected Profit ◽  
Planning Period ◽  
Product Mix ◽  
Supply Disruption ◽  
Content Type ◽  
Disruption Risk ◽  
Dairy Plant ◽  
Planning Decision

Purpose The purpose of this paper is to develop a model for the production planning decision of a dairy plant in a multi-product setting under supply disruption risk and demand uncertainty while determining the optimal product-mix and material planning requirement. Design/methodology/approach A mixed-integer nonlinear programming model is proposed to determine the optimal product-mix that maximizes the expected profit of a dairy. The data are collected through visits to the dairy site, conducting brainstorming sessions with the plant manager and marketing head at the corporate office. Disruption data are collected from the India Meteorological Department, Odisha. Findings From the analysis, it is recommended that the dairy should not produce curd during the planning period. Moreover, turnover from toned, double toned and baby food is maximum than that of the curd and these products are produced in the planning period. The expected profit increases from its present value when an optimal product-mix is followed. Sensitivity analysis is performed to analyze the effect of demand uncertainty, supply disruption and production quota. The expected profit decreases as the supply failure probability increases. Research limitations/implications The model is implemented in a dairy plant under Orissa State Cooperative Milk Producers Federation, Odisha, India. The proposed methodology has not been validated, theoretically. The concerned dairy is based on the Indian context, but the authors believe that the study is highly relevant to other dairies as well. Practical implications This study provides a methodology for dairy plant managers to plan production effectively under supply disruption risk with demand uncertainty. It also suggests material requirement planning at different factories of the dairy plant. Originality/value This paper develops a mathematical model for the production planning decision of a dairy plant that determines the optimal product-mix, which maximizes the expected profit of a dairy under disruption risk and demand uncertainty (in the Indian context).

scholarly journals Unlocking supply chain disruption risk within the Thai beverage industry

2016 ◽  
Vol 116 (1) ◽  
pp. 21-42 ◽  
Author(s):  
Ying Kei Tse ◽  
Rupert L. Matthews ◽  
Kim Hua Tan ◽  
Yuji Sato ◽  
Chaipong Pongpanich
Keyword(s):  
Risk Management ◽  
Demand Uncertainty ◽  
Management Strategies ◽  
Quality Uncertainty ◽  
Supply Disruption ◽  
Content Type ◽  
Beverage Industry ◽  
Increased Risk ◽  
Risk Management Strategies ◽  
Disruption Risk

Purpose – A growing need for global sourcing of business has subjected firms to higher levels of uncertainty and increased risk of supply disruption. Differences in industry and infrastructure make it more difficult for firms to manage supply disruption risks effectively. The purpose of this paper is to extend developing research in this area by addressing gaps within existing literature related to environmental turbulence and uncertainties. Design/methodology/approach – The authors test the model using data collected from 253 senior managers and directors in the Thai beverage industry using advanced statistical techniques to explore the relationship between representations of supply disruption risk and uncertainty. Findings – The results show that both magnitude and probability of risk impact on the disruption risk, but the probability of loss is a dominant determinant. The authors also find that demand uncertainty and quality uncertainty affect the risk perception of purchasing managers, and are related to the magnitude of disruption risk, rather than the frequency of occurrence. Interestingly, the results show that quality uncertainty negatively impacts on the severity of disruption risk. Research limitations/implications – The construct validity of demand uncertainty was under the required threshold, intimating the need for further construct development. Practical implications – The framework provides managers with direction on how to formulate and target their disruption risk management strategies. The work also allows practitioners to critical reflect on implicit risk management strategies they may already employ and their effectiveness. Originality/value – The paper identifies key antecedents of supply disruption risk and tests them within a novel industrial context of the beverage industry and a novel national context of Thailand.

Robust optimization approach to production system with failure in rework and breakdown under uncertainty: evolutionary methods

2015 ◽  
Vol 35 (1) ◽  
pp. 81-93 ◽  
Author(s):  
Masoud Rabbani ◽  
Neda Manavizadeh ◽  
Niloofar Sadat Hosseini Aghozi
Keyword(s):  
Mathematical Model ◽  
Robust Optimization ◽  
Production Planning ◽  
Production System ◽  
Demand Uncertainty ◽  
Optimization Techniques ◽  
Planning Problem ◽  
Optimization Approach ◽  
Content Type ◽  
Evolutionary Methods

Purpose – This paper aims to consider a multi-site production planning problem with failure in rework and breakdown subject to demand uncertainty. Design/methodology/approach – In this new mathematical model, at first, a feasible range for production time is found, and then the model is rewritten considering the demand uncertainty and robust optimization techniques. Here, three evolutionary methods are presented: robust particle swarm optimization, robust genetic algorithm (RGA) and robust simulated annealing with the ability of handling uncertainties. Firstly, the proposed mathematical model is validated by solving a problem in the LINGO environment. Afterwards, to compare and find the efficiency of the proposed evolutionary methods, some large-size test problems are solved. Findings – The results show that the proposed models can prepare a promising approach to fulfill an efficient production planning in multi-site production planning. Results obtained by comparing the three proposed algorithms demonstrate that the presented RGA has better and more efficient solutions. Originality/value – Considering the robust optimization approach to production system with failure in rework and breakdown under uncertainty.

The effect of cultural value orientations on responses to supply-side disruption

2020 ◽  
Vol 40 (11) ◽  
pp. 1723-1747
Author(s):  
Mehrnoush Sarafan ◽  
Brian Squire ◽  
Emma Brandon–Jones
Keyword(s):  
Risk Perception ◽  
Past Research ◽  
Uncertainty Avoidance ◽  
Value Orientations ◽  
Cultural Value ◽  
Supply Disruption ◽  
Content Type ◽  
Disruption Risk ◽  
Supplier Switching ◽  
The Impact

PurposePast research has shown that culture has significant effects on people's evaluation of and responses to risk. Despite this important role, the supply chain risk literature has been silent on this matter. The purpose of this paper is to examine the impact of cultural value orientations on managerial perception of and responses to a supply disruption risk.Design/methodology/approachThe authors conduct a scenario-based experiment to investigate the effect of cultural value orientations – i.e. individualism-collectivism and uncertainty avoidance – on individuals' perception of risk and supplier switching intention in the face of a supply disruption.FindingsThe findings highlight the negative effect of individualism-collectivism on disruption risk perception and switching intention in high uncertain circumstances. However, these relationships are non-significant in relatively less uncertain situations. Moreover, the findings show that the impact of uncertainty avoidance on risk perception and supplier switching is positive and significant in both low and high uncertain circumstances.Originality/valueExtant research has traditionally assumed that when confronted with disruption risks, managers make decisions using an economic utility model, to best serve the long-term objectives of the firm. This paper draws from advances of behavioural research to show that cultural value orientations influence such decisions through a mediating mechanism of subjective risk perception.

Managers' risk perception of supply chain uncertainties

2020 ◽  
Vol 120 (9) ◽  
pp. 1617-1634 ◽  
Author(s):  
Yuji Sato ◽  
Ying Kei Tse ◽  
Kim Hua Tan
Keyword(s):  
Supply Chain ◽  
Risk Perception ◽  
Comparative Studies ◽  
Risk Perceptions ◽  
Structural Model ◽  
Comparative Case Study ◽  
Sustainable Supply Chain ◽  
Supply Disruption ◽  
Content Type ◽  
Disruption Risk

PurposeThis paper provides a practical framework for managers to develop a sustainable supply chain. Given that rapid globalization has increased supply disruption risk, managers have been forced to establish efficient and responsive supply chain strategies. Nevertheless, diverse uncertainty factors, such as risk perception of strategies, have made practical management difficult. Quantifying managers' risk perceptions and applying them to supply chain strategies allows the authors to propose a structural and practical model for managing supply disruption.Design/methodology/approachThe existing structural model is refined by taking subjective factors into account using the analytic hierarchy process. The applicability of the refined model is demonstrated through a comparative case study.FindingsManagers' risk perceptions vary not only among companies but also between managing divisions within a company, which necessitates possible changes in strategy due to environmental turbulence. The principal component analysis (PCA) characterizes managers' risk perceptions that illustrate companies' emphases on disruption risk.Practical implicationsThe proposed approach quantifies risk perception, which enables practitioners to deal with subjective information in quantitative form. Comparative studies clarify differences in perception given different business backgrounds. The results provide managers with in-depth insights for establishing supply chain strategies reflecting their risk perception.Originality/valueQuantification of managers' subjective risk perception clarifies both the trend and the individual features for uncertainties. The results allow the authors to conduct the PCA, which characterizes companies. Comparative studies generalize the results of extant work, shedding light on cross-sectional differences given different business backgrounds. The effectiveness of the approach is confirmed through retrospective interviews with practitioners.

scholarly journals An attention-based view of supply disruption risk management: balancing biased attentional processing for improved resilience in the COVID-19 context

2021 ◽  
Vol 41 (13) ◽  
pp. 152-177
Author(s):  
Harri Lorentz ◽  
Sini Laari ◽  
Joanne Meehan ◽  
Michael Eßig ◽  
Michael Henke
Keyword(s):  
Risk Management ◽  
Management Practices ◽  
Attentional Selection ◽  
Disruption Management ◽  
Supply Risk ◽  
Top Down ◽  
Supply Disruption ◽  
Bottom Up ◽  
Content Type ◽  
Disruption Risk

PurposeIn the context of the COVID-19 pandemic, this study investigates a variety of approaches to supply disruption risk management for achieving effective responses for resilience at the supply management subunit level (e.g. category of items). Drawing on the attention-based view of the firm, the authors model the attentional antecedents of supply resilience as (1) attentional perspectives and (2) attentional selection. Attentional perspectives focus on either supply risk sources or supply network recoverability, and both are hypothesised to have a direct positive association with supply resilience. Attentional selection is top down or bottom up when it comes to disruption detection, and these are hypothesised to moderate the association between disruption risk management perspectives and resilience.Design/methodology/approachConducted at the early phases of the COVID-19 pandemic, this study employs a hierarchical regression analysis on a multicountry survey of 190 procurement professionals, each responding from the perspective of their own subunit area of supply responsibility.FindingsBoth attentional disruption risk management perspectives are needed to achieve supply resilience, and neither is superior in terms of achieving supply resilience. Both the efficiency of the top down and exposure to the unexpected with the bottom up are needed – to a balanced degree – for improved supply resilience.Practical implicationsThe results encourage firms to purposefully develop their supply risk management practices, first, to include both perspectives and, second, to avoid biases in attentional selection for disruption detection. Ensuring a more balanced approach may allow firms to improve their supply resilience.Originality/valueThe results contribute to the understanding of the microfoundations that underpin firms' operational capabilities for supply risk and disruption management and possible attentional biases.

A Linear Programming Model for Product Mix Profit Maximization in A Small Medium Enterprise Company

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
S Mohd Baki ◽  
Jack Kie Cheng
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Business Performance ◽  
Programming Model ◽  
Profit Maximization ◽  
Optimal Level ◽  
Linear Programming Model ◽  
Product Mix ◽  
Small Medium Enterprises ◽  
Medium Enterprises

Production planning is often challenging for small medium enterprises (SMEs) company. Most of the SMEs are having difficulty in determining the optimal level of the production output which can affect their business performance. Product mix optimization is one of the main key for production planning. Many company have used linear programming model in determining the optimal combination of various products that need to be produced in order to maximize profit. Thus, this study aims for profit maximization of a SME company in Malaysia by using linear programming model. The purposes of this study are to identify the current process in the production line and to formulate a linear programming model that would suggest a viable product mix to ensure optimum profitability for the company. ABC Sdn Bhd is selected as a case study company for product mix profit maximization study. Some conclusive observations have been drawn and recommendations have been suggested. This study will provide the company and other companies, particularly in Malaysia, an exposure of linear programming method in making decisions to determine the maximum profit for different product mix.

Minimizing supply chain disruption risk through enhanced flexibility

2009 ◽  
Vol 39 (5) ◽  
pp. 404-427 ◽  
Author(s):  
Joseph B. Skipper ◽  
Joe B. Hanna
Keyword(s):  
Supply Chain ◽  
Multiple Regression ◽  
Planning Process ◽  
Research Effort ◽  
Risk Exposure ◽  
Contingency Planning ◽  
Management Support ◽  
Supply Chain Disruption ◽  
Content Type ◽  
Disruption Risk

PurposeThe purpose of this paper is to examine the use of a strategic approach (contingency planning) to minimize risk exposure to a supply chain disruption. Specifically, the relationship between several attributes of a contingency planning process and flexibility are examined.Design/methodology/approachThis effort develops a model that will provide both researchers and practitioners a means of determining the attributes with the highest relationship to flexibility. The model is then tested using multiple regression techniques.FindingsBased on the sample used in this survey, top management support, resource alignment, information technology usage, and external collaboration provide the largest contributions to flexibility. Flexibility has been shown to enhance the ability to minimize risk exposure in the event of a supply chain disruption.Research limitations/implicationsIn this research effort, the multiple regression results produced an R2 of 0.45, indicating that additional variables of interest may need to be identified and investigated. Furthermore, a wider range of respondents could make the results more generalizable.Practical implicationsThis effort will help to allow managers at multiple levels to understand the primary planning attributes to use to increase flexibility.Originality/valueThe paper develops a model that can be used to identify the specific areas that can lead to improved flexibility. Based on the model, managers, and planners can develop appropriate strategies for minimizing risk exposure in the event of a supply chain disruption.

System dynamics modelling of fixed and dynamic Kanban controlled production systems: a supply chain perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jagan Mohan Reddy K. ◽  
Neelakanteswara Rao A. ◽  
Krishnanand Lanka ◽  
PRC Gopal
Keyword(s):  
Supply Chain ◽  
System Dynamics ◽  
Cycle Time ◽  
Production System ◽  
Demand Uncertainty ◽  
Production Systems ◽  
Decision Variable ◽  
Content Type ◽  
Pull Production ◽  
Kanban System

Purpose Pull production systems have received much attention in the supply chain management environment. The number of Kanbans is a key decision variable in the pull production system as it affects the finished goods inventory (FGI) and backorders of the system. The purpose of this study is to compare the performance of the fixed and dynamic Kanban systems in terms of operational metrics (FGI and backorders) under the demand uncertainty. Design/methodology/approach In this paper, the system dynamics (SD) approach was used to model the performance of fixed and dynamic Kanban based production systems. SD approach has enabled the feedback mechanism and is an appropriate tool to incorporate the dynamic control during the simulation. Initially, a simple Kanban based production system was developed and then compared the performance of production systems with fixed and dynamic controlled Kanbans at the various demand scenarios. Findings From the present study, it is observed that the dynamic Kanban system has advantages over the fixed Kanban system and also observed that the variation in the backorders with respect to the demand uncertainty under the dynamic Kanban system is negligible. Research limitations/implications In a just-in-time production system, the number of Kanbans is a key decision variable. The number of Kanbans is mainly depended on the demand, cycle time, safety stock factor (SSF) and container size. However, this study considered only demand uncertainty to compare the fixed and dynamic Kanban systems. This paper further recommends researchers to consider other control variables which may influence the number of Kanbans such as cycle time, SSF and container size. Originality/value This study will be useful to decision-makers and production managers in the selection of the Kanban systems in uncertain demand applications.

scholarly journals Dynamic Analysis and Optimization of a Production Control System under Supply and Demand Uncertainties

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Qiankai Qing ◽  
Wen Shi ◽  
Hai Li ◽  
Yuan Shao
Keyword(s):  
Control System ◽  
Performance Indicators ◽  
Demand Uncertainty ◽  
Production Control ◽  
Optimal Parameter ◽  
Dynamic Performance ◽  
Random Demand ◽  
Start Time ◽  
Supply Disruption ◽  
Production Control System

This study investigates the dynamic performance and optimization of a typical discrete production control system under supply disruption and demand uncertainty. Two different types of uncertain demands, disrupted demand with a step change in demand and random demand, are considered. We find that, under demand disruption, the system’s dynamic performance indicators (the peak values of the order rate, production completion rate, and inventory) increase with the duration of supply disruption; however, they increase and decrease sequentially with the supply disruption start time. This change tendency differs from the finding that each kind of peak is independent of the supply disruption start time under no demand disruption. We also find that, under random demand, the dynamic performance indicators (Bullwhip and variance amplification of inventory relative to demand) increase with the disruption duration, but they have a decreasing tendency as demand variance increases. In order to design an adaptive system, we propose a genetic algorithm that minimizes the respective objective function on the system’s dynamic performance indicators via choosing appropriate system parameters. It is shown that the optimal parameter choices relate closely to the supply disruption start time and duration under disrupted demand and to the supply disruption duration under random demand.

scholarly journals Achieve a low carbon supply chain through product mix

2017 ◽  
Vol 117 (10) ◽  
pp. 2468-2484 ◽  
Author(s):  
Xu Chen ◽  
Xiaojun Wang
Keyword(s):  
Supply Chain ◽  
Trade Policy ◽  
Carbon Emissions ◽  
Channel Structure ◽  
Low Carbon ◽  
Cap And Trade ◽  
Product Mix ◽  
Content Type ◽  
Carbon Supply ◽  
Trade Offs

Purpose In the era of climate change, industrial organizations are under increasing pressure from consumers and regulators to reduce greenhouse gas emissions. The purpose of this paper is to examine the effectiveness of product mix as a strategy to deliver the low carbon supply chain under the cap-and-trade policy. Design/methodology/approach The authors incorporate the cap-and-trade policy into the green product mix decision models by using game-theoretic approach and compare these decisions in a decentralized model and a centralized model, respectively. The research explores potential behavioral changes under the cap-and-trade in the context of a two-echelon supply chain. Findings The analysis results show that the channel structure has significant impact on both economic and environmental performances. An integrated supply chain generates more profits. In contrast, a decentralized supply chain has lower carbon emissions. The cap-and-trade policy makes a different impact on the economic and environmental performances of the supply chain. Balancing the trade-offs is critical to ensure the long-term sustainability. Originality/value The research offers many interesting observations with respect to the effect of product mix strategy on operational decisions and the trade-offs between costs and carbon emissions under the cap-and-trade policy. The insights derived from the analysis not only help firms to make important operational and strategic decisions to reduce carbon emissions while maintaining their economic competitiveness, but also make meaningful contribution to governments’ policy making for carbon emissions control.

Sign in / Sign up

Export Citation Format

Share Document