Practices for strategic capacity management in Malaysian manufacturing firms

While the notion of manufacturing capabilities is a long-standing notion in research on operations management, its actual implementation and management has been hardly researched. Five case studies in Malaysia offered the opportunity to examine the practice of manufacturing managers with regard to strategic capability management. The data collection and analysis was structured by using the notion of Strategic Capacity Management. Whereas traditionally literature has demonstrated the beneficial impact of an appropriate manufacturing strategy on the business strategy and performance, the study highlights the difficulty of managers to set the strategy, let alone implementing it. This is partly caused by the immense pressure of customers in these dominantly Make-To-Order environments for SMEs. Current concepts for manufacturing capabilities have insufficiently accounted this phenomenon and an outline of a research agenda is presented

A Fuzzy Credibility-Based Chance-Constrained Optimization Model for Multiple-Objective Aggregate Production Planning in a Supply Chain under an Uncertain Environment

In this study, a Multiple-Objective Aggregate Production Planning (MOAPP) problem in a supply chain under an uncertain environment is developed. The proposed model considers simultaneously four different conflicting objective functions. To solve the proposed Fuzzy Multiple-Objective Mixed Integer Linear Programming (FMOMILP) model, a hybrid approach has been developed by combining Fuzzy Credibility-based Chance-constrained Programming (FCCP) and Fuzzy Multiple-Objective Programming (FMOP). The FCCP can provide a credibility measure that indicates how much confidence the decision-makers may have in the obtained optimal solutions. In addition, the FMOP, which integrates an aggregation function and a weight-consistent constraint, is capable of handling many issues in making decisions under multiple objectives. The consistency of the ranking of objective’s important weight and satisfaction level is ensured by the weight-consistent constraint. Various compromised solutions, including balanced and unbalanced ones, can be found by using the aggregation function. This methodology offers the decision makers different alternatives to evaluate against conflicting objectives. A case experiment is then given to demonstrate the validity and effectiveness of the proposed formulation model and solution approach. The obtained outcomes can assist to satisfy the decision-makers’ aspiration, as well as provide more alternative strategy selections based on their preferences

Perencanaan Produksi Makanan Laut dengan Pertimbangan Permintaan dan Kapasitas

The sea holds many resources that are very important for life, and one of them is the potential of fisheries, which is a basic human need. Indonesia, as a maritime country whose waters cover 2/3 of its territory, most of its people who live in coastal areas have utilized this condition by conducting fisheries management activities. However, the process still needs technical support to optimize the results. This research will review the production planning process of processed marine products under demand uncertainty. This research will construct a model to minimize production costs by considering demand uncertainty. The model will be computed using Mixed Integer Linear Program (MILP) method to provide the decision of processed products produced and the amount of production

The value of coordination in a two echelon supply chain: Sharing information, policies and parameters.

We study a coordination scheme in a two echelon supply chain. It involves sharing details of replenishment rules, lead-times, demand patterns and tuning the replenishment rules to exploit the supply chain's cost structure. We examine four different coordination strategies; naïve operation, local optimisation, global optimisation and altruistic behaviour on behalf of the retailer. We assume the retailer and the manufacturer use the Order-Up-To policy to determine replenishment orders and end consumers demand is a stationary i.i.d. random variable. We derive the variance of the retailer's order rate and inventory levels and the variance of the manufacturer's order rate and inventory levels. We initially assume that costs in the supply chain are directly proportional to these variances (and later the standard deviations) and investigate the options available to the supply chain members for minimising costs. Our results show that if the retailer takes responsibility for supply chain cost reduction and acts altruistically by dampening his order variability, then the performance enhancement is robust to both the actual costs in the supply chain and to a naïve or uncooperative manufacturer. Superior performance is achievable if firms coordinate their actions and if they find ways to re-allocate the supply chain gain.Bullwhip; Global optimisation; Inventory variance; Local optimisation; Supply chains; Studies; Coordination; Supply chain; IT; Replenishment rule; Rules; Demand; Patterns; Cost; Structure; Strategy; Retailer; Policy; Order; Variance; Inventory; Costs; Options; Variability; Performance; Performance enhancement; Firms;

Differentiation vs. standardisation in supply chain segmentation: a quantitative study

The key value proposition of supply chain segmentation is to differentiate supply chains through a reasonable number of segments in order to gain a level of standardisation and avoid managerial complexity incurred in fully customised supplychains. The decision on how products are grouped into segments is at the core of a successful implementation. A fundamental trade-off in this decision-making process is between higher differentiation by having small group sizes and higher standardisation from a smaller number of groups. In this manuscript, we implement segmentation on supply chain configurations and investigate the trade-off by analysing several network scenarios. We use optimisation models for each scenarioto align decisions of segment formation and supply chain configurations. We show that divergences in demand characteristics, geographic difference, and cost synergy such as pooling effect have impacts on the balance of standardisation and differentiation

An optimal-control based integrated model of supply chain

Problems of supply chain scheduling are challenged by high complexity, combination of continuous and discrete processes, integrated production and transportation operations as well as dynamics and resulting requirements for adaptability and stability analysis. A possibility to address the above-named issues opens modern control theory and optimal program control in particular. Based on a combination of fundamental results of modern optimal program control theory and operations research, an original approach to supply chain scheduling is developed in order to answer the challenges of complexity, dynamics, uncertainty, and adaptivity. Supply chain schedule generation is represented as an optimal program control problem in combination with mathematical programming and interpreted as a dynamic process of operations control within an adaptive framework. The calculation procedure is based on applying Pontryagin’s maximum principle and the resulting essential reduction of problem dimensionality that is under solution at each instant of time. With the developed model, important categories of supply chain analysis such as stability and adaptability can be taken into consideration. Besides, the dimensionality of operations research-based problems can be relieved with the help of distributing model elements between an operations research (static aspects) and a control (dynamic aspects) model. In addition, operations control and flow control models are integrated and applicable for both discrete and continuous processes.supply chain, model of supply chain scheduling, optimal program control theory, Pontryagin’s maximum principle, operations research model,

Challenges in forecasting uncertain product demand in supply chain: A systematic literature review

Forecasting for uncertain product demand in supply chain is challenging and statistical models alone cannot overcome the challenges faced. Our overall objective is to explore the challenges faced in forecasting uncertain product demand and examine extant literature by synthesizing the results of studies that have empirically investigated this complex phenomenon. We performed a Systematic Literature Review (SLR) following the well-known guidelines of the evidence-based paradigm which resulted in selecting 66 empirical studies. Our results are presented into two categories of internal and external challenges: 24 of the 66 studies express internal challenges, whilst 13 studies report external challenges, and 8 studies cover both internal and external challenges. We also present significant gaps identified in the research literatur