Production Planning

The vendor selection process has undergone significant changes during the past twenty years. These include increased quality guidelines, improved computer communications, and increased technical capabilities. Given radical changes in the purchasing selection process, it is appropriate to review the past research and to determine its relevance to the supplier selection decision. This paper reviews, annotates, and classifies 74 related articles which have appeared since 1966. Specific attention is given to the criteria and analytical methods used in the vendor selection process. In response to the increased interest in Just-In-Time (JIT) manufacturing strategies, and analysis of JIT's impact on vendor selection is also presented. Finally, conclusions and potential areas for future research are presented.

planning compared to relatively constant demand. Varying the demand size will affect theavailability of raw materials, production scheduling, and financial planning of a company.These impacts of fluctuated demand will affect much in the Small and Medium Enterprises(SME) which have limited resources. These companies require a production plan that cananticipate fluctuating demands to minimize stock out and over stock of the products.Aggregate-disaggregate planning is a method that can solve the problem. This study discussesproduction planning using Aggregate-disaggregate Planning method in a production systemwith fluctuated demand. The case study organization is a SME that manufactures furnitureproducts. The objective is to develop a production planning using Aggregate-disaggregatePlanning Method in order to determine the kind of products to be made for the coming periodto anticipate fluctuated demand. The data collection is conducted at the case studyorganization such as demand and p...

The success of a company is measured by the ability to provide goods and services at the right time and place. Besides, one of the factors of the company's progress is also supported by inventory management which functions to control the company's inventory by neither hoarding lots of products nor running out of products. The development of technology requires a company's inventory management that is fast, precise and accurate to support its' performance. In fact, some companies have difficulty in determining the stock of their goods production so that it impedes the fulfillment of consumer needs in the event of high market demand. This study is to determine the reorder point stock of a company that determines the number of purchases and sales of the company's products, therefore the amount of expenses and income can be presented to the board of directors to be followed up quickly and accurately. The method used is a statistical approach to the economic quantity model where safety stock analysis is first performed. This method is used to put the company's products to the inventory so that there are no excess or even shortages of products. System development method used is a user centered design, which is the most suitable to the study. The output of the activity is information in the form of advice to the company leaders in making decisions about production planning, controlling stock inventory, detailing market demand quickly, precisely and accurately and developing a decision support system that is made by taking into account the details of user needs.

This paper presents a review of mathematical programming models for supply chain production and transport planning. The purpose of this review is to identify current and future research in this field and to propose a taxonomy framework based on the following elements: supply chain structure, decision level, modeling approach, purpose, shared information, limitations, novelty and application. The research objective is to provide readers with a starting point for mathematical modeling problems in supply chain production and transport planning aimed at production management researchers.

Lot sizing is one of the most important and also one of the most di cult problems in production planning. This subject has been studied extensively in the literature. In this article, we consider single-level lot sizing problems, their variants and solution approaches. After introducing factors a ecting formulation and the complexity of production planning problems, and introducing di erent variants of lot sizing and scheduling problems, we discuss single-level lot sizing problems, together with exact and heuristic approaches for their solution. We conclude with some suggestions for future research. ?

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.

This article analyzes design changes in the scenario of information technology (IT), Industry 4.0 and the subsequent integration of production and consumption systems. Taking the network as the organizational paradigm characteristic of current conditions, it defines the concept of design networks and analyzes the effects of social and technological developments on practice. Through the presentation of different cases, it will also describe open design as one of the most common approaches employed in design networks by examining its contribution to the fourth industrial revolution. Finally, this article discusses the roles that the designer takes on: designer-entrepreneur, design culture specialist and metadesigner.

Purpose-The objectives of this study were to calculate the forecast demand and to develop aggregate production planning for PT XYZ to meet demand with the lowest cost.Methodology–The data were gathered through literature review and secondary data gathered directly from the company itself. The demand data from past three years was used to forecast demand using decomposition, seasonal variation, and multiple regression method. Furthermore, all data were analyzed and used to design aggregate planning by using three strategies namely Chase, Level, and Mixed strategy.Finding–The result of this study shows that the seasonal variation method is the best method to use for forcast the demand on 2019, and chase strategyis the optimal strategy for aggregate production planning. Keywords:     heuristic method, production planning, aggregate planning, forecasting

Providing production forecasts of main food commodities to food security planners may lead to improved production planning decisions in any country or region. Cognizant of this fact, this study forecasts the future wheat production gaps (PG) in Pakistan for 13 years (2013-2025) at two different levels of consumption, i.e. 125 kg/capita/annum and 150 kg/capita/annum. Findings of the study reveal that at the level of 125 kg/capita/annum, the gap between wheat grain availability and national requirement will increase from -0.17 million tonnes (MT) in 2013 to around -0.50 MT in 2025. Likewise, at the level of 150 kg/capita/annum, the gap will increase from nearly -5.0 MT in 2013 to almost -7.0 MT in 2025. It implies that PG will deepen in coming years that will increase the chances of higher food insecurity in the country. In view of this, planners need to revamp their strategies to cope with future food insecurity challenges.

Production engineers are urged to take ergonomic considerations into account when planning for production. However, the means to do so are often inadequate with respect to training as well as support. There is a lack of methods to predict, at a reasonable cost, biomechanical load on an operator performing a task not yet observable on a product and in a workplace not yet existing. The purpose of this study was to develop an ergonomic complement to a modern MTM system called SAM that gives the production engineer a first insight into the future ergonomic quality of a planned production. A method was developed that requests the engineer to supply two additional pieces of information to the analysis: the zone relative to the operator's body in which the movement takes place or ends, and the weight or force involved in the operation. As method of comparison for validation purposes was selected the operator selfevaluation method VIDAR. The method was tested at the Torslanda final assembly plant of Volvo Car Corporation and at the ITT Flygt plant for large submersible pumps at three different balances and compared with two different methods of assessing biomechanical load. The results show that the method identifies the events causing high biomechanical load on the operator so that they can be redesigned. The suggested method has proven to be a useful tool and is being introduced at Volvo Car Corporation.

In this report, a production system of a coffee cups factory is used as a case for simulation modelling and productivity optimization. The study is based on Bank’s simulation project methodology to systematically approach optimum results, while the theory of constraints (TOC) is used as the main framework for the iterations of the production system improvements. The findings prove how simulation modelling and TOC can improve the productivity of the production system dramatically by surgically aligning investments to even out the system capabilities.

The paper deals with lot sizing and scheduling problem (LSSP) of a multi-site manufacturing system with capacity constraints and uncertain multi-product and multi-period demand. LSSP is solved by an hybrid model resulting from the integration of a mixed-integer linear programming model and a simulation model.

The consideration of uncertainty in manufacturing systems supposes a great advance. Models for production planning which do not recognize the uncertainty can be expected to generate inferior planning decisions as compared to models that explicitly account for the uncertainty. This paper reviews some of the existing literature of production planning under uncertainty. The research objective is to provide the reader with a starting point about uncertainty modelling in production planning problems aimed at production management researchers. The literature review that we compiled consists of 87 citations from 1983 to 2004. A classification scheme for models for production planning under uncertainty is defined. r (J. Mula). Analytical models [3] 3. Material requirement planning Conceptual models [9] Analytical models [6] Artificial intelligence models [4] Simulation models [10] 4. Capacity planning Analytical models [4] Simulation models [1] 5. Manufacturing resource planning Analytical models [7] Artificial intelligence models [5] Simulation models [2] 6. Inventory management Analytical models [10] Artificial intelligence models [5] 7. Supply chain planning Conceptual models [1] Analytical models [5] Artificial intelligence models [5] J. Mula et al. / Int. J. Production Economics 103 (2006) 271-285 272

Many decisions in operations management (OM) belong to the class of Non-deterministic Polynomial hard problems and thus heuristic search methods have been applied to improve OM decisions. While genetic algorithms (GAs) are promising tools for searching fast and good solutions in diverse OM areas, future research will benefit from a review of the OM problems solved by GAs. The purpose of this paper is to review the literature on OM with GA-based solutions and to suggest possible gaps from the point of view of researchers and practitioners. A total of 119 peer reviewed journal papers published from 2007 to 2017 are reviewed and analysed methodologically. The applications of GAs in OM are categorized into process and product design, operations planning and control, and operations improvement. Observations from the existing literature are presented and future research directions are suggested. Although GAs have been one of the most popular heuristic approaches for optimization, there are OM problems that are yet to be investigated. The findings of this review pave the path for future research to apply GAs to solve OM problems.

This paper illustrates the results of an empirical study involving 21 engineer-to-order (ETO) companies, operating in the machinery-building industry. The study investigates the needs and requirements of such companies in terms of software support for governing the businesses, with particular emphasis on production planning and control (PPC) processes. An empirical analysis investigated two main aspects: (i) the set of business activities performed by the companies in the analysed industry and (ii) the relevant, high-level software functionalities required for the execution of such activities. As an answer to the observed compelling need for reviewing the general approaches to PPC in machinery-building companies, we develop an empirical, high-level production planning and scheduling reference framework, encompassing all the activities involved in the order fulfilment process.

Engineer-to-order (ETO) production planning and control: an empirical framework for machinery-building companies. Available from: https://www.researchgate.net/publication/276274086_Engineer-to-order_%28ETO%29_production_planning_and_control_an_empirical_framework_for_machinery-building_companies [accessed May 14, 2015].

The pressures from free trade in year 2005 has urged all Thailand's textile manufacturers to improve their competitiveness. The benchmarking survey depicts Thailand's On Time Performance index (OTP) as a problem and that it lags behind Asian leaders such as Singapore and Indonesia. Supply Chain Management, as a new industrial-wide management strategy, has become a solution to improve competitiveness as well as reduce lead time. From our pilot study in supply chain implementation project under the Thailand Textile Institute, it has shown that there are three major uncertainties- demand, supplier, process and control uncertainties- affecting customer lead time. Apart from that, information sharing within an organization and between supply chain echelons, particularly in order processing, raw material sourcing and production planning process are significant in managing efficient supply chain. In this paper, we show how to apply the supply chain management concept in four text...

O presente artigo tem como objetivo estudar algumas das principais características do modelo de produção por encomenda Make-to-Order o qual foi comparado com outros modelos de grande divulgação na indústria como o Assemble-to-Order, Engineer-to-Order e o Make-to-Stock. Apresenta-se as exigências da cadeia de suprimentos de indústrias com cenário MTO e a capacidade de produção também é detalhada do ponto de vista dos seus requisitos.

This article presents a study about the main features of the Make-to-Order production Model and a comparison with other widely known models like Assemble-to-Order, Engineer-to-Order and Make-to-Stock. It is presented some characteristics and challenges of Make-to-Order industries on a Supply Chain point of view as well as constraints faced by the production capacity.

A state of the art of a particular planning problem, the single item lot sizing problem (SILSP), is given for its uncapacitated and capacitated versions. First classes of lot sizing problems are briefly surveyed. Various solution methods for the Uncapacitated Single Item Lot Sizing Problem (USILSP) are reviewed. Four different mathematical programming formulations of the classical problem are presented. Different extensions for real-world applications of this problem are discussed. Complexity results of the capacitated Single Item Lot Sizing Problem (CSILSP) are given together with its different formulations and solution techniques.

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multiperiod, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers' zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.

Driven by a real-world application in the beverage industry, this paper provides a design of a new VNS variant to tackle the annual production budget problem. The problem consists of assigning and scheduling production lots in a multi-plant environment, where each plant has a set of filling lines that bottle and pack drinks. Plans also consider final product transfers between the plants. Our algorithm fixes setup variables for family of products and determines production, inventory and transfer decisions by solving a linear programming (LP) model. As we are dealing with very large problem instances, it is inefficient and unpractical to search the entire neighborhood of the incumbent solution at each iteration of the algorithm. We explore the sensitivity analysis of the LP to guide the partial neighborhood search. Dual re-optimization is also used to speed-up the solution procedure. Tests with instances from our case study have shown that the algorithm can substantially improve the current business practice, and it is more competitive than state-of-the-art commercial solvers and other VNS variants.

En este trabajo se presenta un modelo de optimización desarrollado para planificar la producción de productos y subproductos derivados de las canales de cerdo. Las restricciones del modelo establecen los tiempos de operación de la planta, capacidad de producción, límite de producción de productos y subproductos, balance de inventario, capacidad de almacenamiento y capacidad de congelación, entregando como resultado los lotes óptimos de producción, niveles de inventario fresco y congelado para productos y subproductos, las ventas a realizar, la demanda insatisfecha y la capacidad de almacenamiento a tercerizar. Este modelo fue aplicado usando los datos de una planta faenadora de carne de cerdo localizada en la Región del Maule, Chile, para la temporada 2009 y 2010. Los resultados indican una reducción de los costos asociados a tiempos de proceso y utilización de mano de obra del 25%, y una reducción de la capacidad de almacenamiento a subcontratar del 40%.

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.

This paper presents an interactive model based system for the management of production in textile production systems focusing on the Master Production Scheduling problem. Because of the special characteristics of the industry, that is mainly the multi-phase process with multiple units per phase, different planning horizons and different production requirements for each phase, the scheduling of these systems becomes quite complex. Apart from a comprehensive presentation of the set of the modules the system is composed of, together with their interrelationships, the above characteristics are analyzed, and their impact on the production control system is explained. The system is also related to two well-known production control systems, namely MRP-II and Optimised Production Technology. The system's attributes are presented with the aid of data structure diagrams, while the complete algorithm concerning the Master Production Scheduling module, in a pseudo-code form, and the corresponding part of the database are illustrated in Appendix A.

The classical market economy provided basis for emergence of a throwaway society that is based on economies of scale, manufacturing of short-lived average quality products, planned obsolescence and consequent ever-growing demand of consumers for new products and services. This society is clearly unsustainable. An alternative model is the so-called circular economy based on optimised product life span, extended services and remanufacturing activities. The aim of this paper is to understand the complexity of the product durability discourse from environmental and economic perspectives and from the viewpoint of different stakeholders and to discuss innovative strategies that can address some of the identified eco-design bottlenecks in product durability by maximising utilisation rate and improving value of durable products for users, which altogether can contribute to understanding of how the alternative model of circular economy could be facilitated. The ideas outlined in the paper can be of interest for strategic product designers, business managers and for environmental managers of companies that either produce durable products or deliver services of durable products.

The paper analyses the introduction of a platform strategy in new product development with reference to its application in the automobile industry. A definition of platform and associated core concepts such as product architecture, modularisation and standardisation is given. The implication and benefits of a platform strategy are then discussed both from the technical and organisational points of view. The evolution of product development through the adoption of a platform strategy in Japanese automobile firms is also analysed.

T he purpose of this paper is to develop an approach to a resource-allocation problem that typically appears in organizations with a centralized decision-making environment, for example, supermarket chains, banks, and universities. The central unit is assumed to be interested in maximizing the total amount of outputs produced by the individual units by allocating available resources to them. We will develop an interactive formal approach based on data envelopment analysis (DEA) and multiple-objective linear programming (MOLP) to find the most preferred allocation plan. The units are assumed to be able to modify their production in the current production possibility set within certain assumptions. Various assumptions are considered concerning returns to scale and the ability of each unit to modify its production plan. Numerical examples are used to illustrate the approach.

Long-and medium-term production planning are tools to match production orders with resource capacity and that can also be used as a baseline for material procurement. The lack of a detailed schedule for the manufacturing operations, however, may cause difficulties in providing a proper material requirements planning and may affect the feasibility of the production plan itself. This paper proposes an approach, based on production process knowledge, to extract scheduling information from an aggregate production plan in order to support material procurement. The proposed approach is applied to an industrial case involving machining center production.

There is robust evidence that the level of implementation of the Last Planner® System (LPS) is increasing geographically and geometrically in construction. The International Group for Lean Construction (IGLC) community has reported this growth at IGLC conferences over this period. However, no study has explored how the LPS and its implementation has developed or improved.
This study explored developments in the LPS from the review of IGLC conference papers. Qualitative research design utilising content analysis was adopted for this study comprising 57 IGLC reports on LPS implementation across 16 countries. The study reveals components of LPS implemented, with measuring of PPC, Weekly Work Planning meeting and recording reasons for non-completion the most reported. The study developed a timeline for the LPS development and revealed that some of the papers reviewed have no defined methodology.
The study concludes that the LPS has developed in terms of its level of implementation, theory development, and as a vehicle to improve construction management practice across the major continents of the world, with elements that had little presence at the onset now prominent. The study recommends that more attention should be given to the relationship between practical applications and research methods to aid the establishment of sound theory to improve practice.

Much of the research on mass customization strategy implementation reflects a functional focus, considering product design, marketing, manufacturing or sourcing, individually. This paper takes a step towards integrating these perspectives into a more systemic view of mass customization strategy implementation. More precisely, the paper explores how a firm's supply chain -meant as the whole of its supply, manufacturing and distribution networks -should be configured when different degrees of customization are offered. The empirical research consists of a multiple case study including firms in the telecommunications, transportation vehicles and food processing equip-ment industries. Case analyses highlighted that the degrees of freedom customers have in specifying product features, heavily affects the supply-chain configuration, as well as product architecture and, ultimately, firm performances. Our findings further show that two peculiar supply-chain configurations can be identified, each one suggesting an isomorphism between market characteristics, product structure and supply-chain configuration.

This article surveys the recently emerged field of reverse logistics. The management of return flows induced by the various forms of reuse of products and materials in industrial production processes has received growing attention throughout this decade. Many authors have proposed quantitative models taking those changes in the logistics environment into account. However, no general framework has been suggested yet. Therefore the time seems right for a systematic overview of the issues arising in the context of reverse logistics. In this paper we subdivide the field into three main areas, namely distribution planning, inventory control, and production planning. For each of these we discuss the implications of the emerging reuse efforts, review the mathematical models proposed in the literature, and point out the areas in need of further research. Special attention is paid to differences and/or similarities with classical 'forward' logistics methods. © 1997 Elsevier Science B.V.

This paper presents a framework for a dynamic integrated production planning and inventory control system. The IPPIC system is integrated with the existing Enterprise Resource Planning (ERP) system to generate feasible, constrained operational production plans and replenishment schedules. The suggested framework considers production quantity constraints, safety stock requirements, and demand fluctuations. The framework is applied for a single line, multi-stage, multi-product edible oil processing firm. Due to process requirements, a push-pull point is established in the production line. Basic products are "pushed" to inventory according to a master schedule based on forecasts, then final products are "pulled" or customized to order. Also, the existance of co-products and their impact has been addressed. The proposed system is expected to improve customer service level and cost reduction.

Quantity discount is considered to encourage the producer to order more quantities.Interrelationship between lead time, transportation cost, and GHGs is considered.Demand uncertainty is assumed to follows a pre-specified distribution function.Shortages are penalized by a generic nonlinear multiple breakpoint function.The concepts of GHG emission and waste management are incorporated into the model.In this paper we develop a stochastic programming approach to solve a multi-period multi-product multi-site aggregate production planning problem in a green supply chain for a medium-term planning horizon under the assumption of demand uncertainty. The proposed model has the following features: (i) the majority of supply chain cost parameters are considered; (ii) quantity discounts to encourage the producer to order more from the suppliers in one period, instead of splitting the order into periodical small quantities, are considered; (iii) the interrelationship between lead time and transportation cost is considered, as well as that between lead time and greenhouse gas emission level; (iv) demand uncertainty is assumed to follow a pre-specified distribution function; (v) shortages are penalized by a general multiple breakpoint function, to persuade producers to reduce backorders as much as possible; (vi) some indicators of a green supply chain, such as greenhouse gas emissions and waste management are also incorporated into the model. The proposed model is first a nonlinear mixed integer programming which is converted into a linear one by applying some theoretical and numerical techniques. Due to the convexity of the model, the local solution obtained from linear programming solvers is also the global solution. Finally, a numerical example is presented to demonstrate the validity of the proposed model.

This paper presents research results that describe how value generation can be improved in the design process of industrial projects when using computer advanced visualization tools
CAVT. The CAVT concept definition, prior studies about impacts of CAVT, and why they are not sufficient are presented in the paper, supporting the assertion that the extensive attention to technology instead of to the context of technology application and the lack of a conceptual framework has prevented some prior research about CAVT impacts to truly focus in ideas about how to improve engineering and construction processes. Combining production theory and lean construction principles with information technology
IT, a framework for understanding the impacts of CAVT developed as part of the research is proposed. Illustration of the use of the framework in a case study and research validation activities leads to analytic generalization of the research results.

Introduction: Material Requirement Planning (MRP) is a technique or a logical procedure to translate the Master Production Schedule (MPS) of the finished goods or end item into the net requirements for some of the components needed to implement the MPS. MRP is used to determine the amount of material needs to support the Master Production Schedule and when the material needs to be scheduled.Methods: The study is conducted on 13 August 2018 until 12 September 2018 at the installation Nutrition RSIA Kendangsari Merr Surabaya. Collecting data in this study using several methods, including: observation- This stage is conducted in all parts related to the object of study, starting from the Purchase Order (PO) by a head cook up to raw material stored in the storage, discussion- author interviews and collects data to communicate and discuss with the respondents. Respondents in this study are the head of the nutrition unit and head cook of RSIA who have the authority doing the purchasing.Re...

Semakin ketat dan kompetitifnya persaingan industri di Indonesia menuntut para pelaku bisnis untuk meningkatkan efektifitas dan efisiensi di segala bidang. Begitu pula yang terjadi padaPT. Fremont Nusametal yang bergerak pada industri peleburan logam dengan menghasilkan produk tembaga dan aluminium.Seiring dengan permintaan yang cenderung meningkat, maka permasalahan yang berkaitan dengan produksi mulai muncul.Salah satunya adalah kurangnya tenaga kerja di saat permintaan yang cukup tinggi. Perencanaan produksi usulan pada penelitian ini dimulaidengan peramalan permintaan dengan menggunakan metode moving average (MA), weighted moving average (WMA), dan exponential smoothing (ES). Dari ketiga metode tersebut dipilih salah satu metode yang hasilnya dapat digunakan sebagai data permintaan dalam perencanaan produksi agregat. Hasil perencanaan produksi agregat menggunakan metode heuristikdan transportasi dengan pendekatan simulasi dibandingkan dengan total biaya produksi dan rata-rata kekurangan aktual setiap periode dari perencanaan produksi perusahaan.Sehingga diperoleh rencana produksi untuk periode Januari -Desember 2014 dengan total biaya produksi antaraRp 14.354.500.530,00-Rp14.356.452.702,00 dan rata-rata kekurangan aktual setiap periodenya antara 2072,5 jam-5696,3jam. Sedangkan untuk perencanaan produksi perusahaan diperoleh total biaya produksi sebesar Rp 13.500.223.744,00 dengan rata-rata kekurangan aktual setiap periode antara 4666,8jam -8290,6jam.

Enterprise Resource Planning (ERP) systems like SAP R/3 ® are business software tools that help managing important parts of business, including e.g. product planning, parts purchasing, maintaining inventories, interacting with vendors, customer service, and tracking orders. These systems provide a complete infrastructure for enterprise corporate information processing and the capability of integrating and summarizing detailed data to produce relevant management information. Current ERP systems do not support automatic discovery and extraction of knowledge from data. Due to increasing complexity of transactions and short resources conventional reporting is often not enough to maintain a sufficient competitive advantage. The application of Business Intelligence for the efficient solution of problems in different economic areas is mandatory. Vendor evaluation has been proved as an effective method of cost reduction. Through proper management, vendors and buyers can achieve significant performance improvement and cost reduction that will result in the development of stronger vendor partnerships. The advanced analyses facilities presented in this paper are based on SAP R/3 ® MM Module data. The presented product is an integrated software solution that provides a flexible reporting and analysis environment for the purchasing department. The use of advanced analytics for vendor behaviour modeling gives the end user a powerful tool for managing vendor relationships. The product is based on a distributed system architecture. It has three main components: a data base with flexible interfaces to the central SAP R/3 ® system and to external data, a powerful data mining tool, and a web enabled end user environment supporting an easy access through the browser of the SAP R/3 ® client.

The management of food distribution networks is receiving more and more attention, both in practice and in the scientific literature. In this paper, we review quantitative operations management approaches to food distribution management, and relate this to challenges faced by the industry. Here, our main focus is on three aspects: food quality, food safety, and sustainability. We discuss the literature on three decision levels: strategic network design, tactical network planning, and operational transportation planning. For each of these, we survey the research contributions, discuss the state of the art, and identify challenges for future research.

The paper reviews about the data mining tasks and methods, and its application in production planning and scheduling. Data mining will be reviewed in four classifications of data mining systems according to the kinds of databases mined, knowledge to discover, techniques utilized and the applications adapted. This paper also reviews in production planning and scheduling that focused in time frame range either short- to mid-range or long-range planning. In production planning, there are a lot of planning such as process planning, strategic capacity planning, aggregate planning, master scheduling, material requirements planning and order scheduling. From these activities different problems are arise because of the different time, product and environment of production.

The paper investigates how the decision variables of the production planning process for a network of "rms in the textile-apparel industry, i.e. planning period length, material availability, the link between production orders and customer orders as regards colour mix, can a!ect the system's time performance, whose measurement has involved the creation of two new indicators. To adhere to reality, we studied and collected actual data from one of the most important Italian companies, the Benetton Group SpA and using these observations as a basis, a simulation model was built. Only the production planning period compression has been recognised as yielding a signi"cant improvement in the external time performance. A relation between the external time performance and the internal time performance of the network is recognised. The cash #ows associated with di!erent lengths of the production planning period are analysed. (A. De Toni) 0925-5273/00/$ -see front matter

This paper shows that managerial questions are not answered satisfactorily with the mathematical interpretation of sensitivity analysis when the solution of a linear programing model is degenerate. Most of the commercially available software packages provide sensitivity results about the optimality of a basis and not about the optimality of the values of the decision variables. The misunderstanding of the shadow price and the validity range information provided by a simplex based computer program may lead to wrong decision with considerable financial losses and strategic consequences. The paper classifies the most important types of sensitivity information, graphically illustrates degeneracy, and demonstrates its effect on sensitivity analysis. A production planning example is provided to show the possibility of faulty production management decisions when sensitivity results are not understood correctly. Finally the recommendations for the users of linear programing models and for software developers are provided.

Businesses must use their resources optimum in order to minimize their costs. Thus, it is important to prepare the strategic plans made as the closest to the truth. Furthermore, in order their works to be sustainable, the companies should plan the future not the present; must take necessary measures to manage the cost of the inventory, labor, time, and financial resources in the best way and to avoid wastage. Demand forecasting systems, besides providing the company keeping up with changing market conditions easily, provides convenience to the company in operational applications with its strategic and managerial level plans. As the demand forecasting performance goes down, the rate of fulfillment the demands of the customer on time goes down. As a result, the companies head for accelerated services with quickly obtainable results, and other costly actions.
The starting point of short-and long-term plan is the forecast demand. Also, as the deviations in long-term plans are high, the determination of the control frequency and methods of the plans are very significant for a successful demand forecasting system. No matter how successful strategic plannings are done, the mistakes in the practice can drag all of the plans towards failure. Therefore, in our study, numerical and non-numerical of demand forecast models will be referred, and there will be comments about a demand forecasts method in a business with the case analysis method and suggestions for improvement.

The purpose of this paper is to ask the questiondoes mass customization really hold the key to customer value? It is argued that while mass customization can, and often does, increase the value of an offering, it is not always the case. In other words, mass customization does not represent the best strategy for all firms in all cases. It is critical that manufacturing firms understand whether their customers (existing and potential) really do value customization. The paper introduces the responsive agility tool that may provide the basis for an informed decision. The tool differentiates a number of value criteria and a method of selecting between them. Further, the tool identifies four levels of customization distinguished by secondary value criteria. We provide a case study demonstrating how the tool may operate in practice. The case study suggests that the tool may effectively differentiate customer types according to their value criteria. Finally the paper proposes that a value judgement is dependent on the negotiated process between a manufacturer and customer.

Cross-functional integration offers numerous, well-documented benefits for newproduct development (NPD), but it also can carry significant costs. Joint involvement of R&D, manufacturing, and marketing personnel can increase the quality, the manufacturability, and the marketability of the final product. However, building consensus among these groups, with their differing perspectives and goals, may require time-consuming meetings as well as tremendous finesse from the managers who guide the NPD effort. Those managers require an approach to cross-functional integration that strikes a balance between efficiency and effectiveness. X. Michael Song, R. Jeffrey Thieme, and Jinhong Xie propose that the right mix of cross-functional involvement may differ depending on the stage in the NPD process. They also suggest that blindly promoting the involvement of all functional areas in all stages of the NPD process may actually decrease NPD performance. They test these propositions in a study that examines the relationships between new product performance and cross-functional joint involvement between R&D, manufacturing, and marketing in five major stages of the NPD process: market opportunity analysis, planning, development, pretesting, and launch. Their objective in this study is to identify patterns of effective crossfunctional involvement in different NPD stages. The study uses data collected from 236 managers working in the R&D, manufacturing, and marketing departments of 16 Fortune 500 firms. Their findings suggest that new-product success may be more likely when a firm employs function-specific and stage-specific patterns of cross-functional integration than it is when the firm attempts to integrate all functions during all NPD stages. For example, during the market opportunity analysis stage, the findings suggest that joint involvement between R&D and marketing may be productive, but joint involvement between R&D and manufacturing and among all three functions may be counterproductive. The results also indicate that joint involvement among all three functions either does not have a significant effect on new product success or may be counterproductive in all stages of the NPD process. For the firms in this study, the three functions seem to take turns playing the central role in cross-functional activities. During the product planning, development, and testing phases, the role of the focal function, or communication hub, shifts from manufacturing to R&D and then to marketing.

The world needs to reduce its dependency on fossil fuel (non-renewable energy) as it is fast depleting and due to the harmful impact to the environment – most notably ‘Climate Change’. Therefore, Green Technology now becomes an even greater significance. We expect that academic scientists, leading engineers, industry researchers and scholar students would exchange and share their experiences and discuss research results on how we can survive and sustain in the future with green technology. The issues are not only about developing technologies, but also how to manage them properly in order to gain maximum benefit for the societies.

This volume contains papers accepted to The 3rd International Conference on Technology and Operations Management (ICTOM 2012) which themed Sustaining Competitiveness through Green Technology Management. The conference was held in East Hall – ITB and SBM-ITB (School of Business and Management – ITB) on July 4-6, 2012.

Nowadays, the entire world is experiencing very complex and chaotic economic situations. Despite the global economic slowdown, it is very encouraging for us to receive over than one hundred submissions from various countries, and accept less than three-fourth submitted papers written by one hundred forty-eight authors for oral presentation to share their knowledges. We are also very grateful for the acceptance of keynote speakerships by well-known senior researchers and international as well as regional practicioners in Technology and Operations Management discipline specifically in Green Technology Management area.

ICTOM 2012 was organized by SBM-ITB, especially Operations and Performance Management (OPM) Interest Group. This conference shows our third collaboration with the esteemed College of Business – Universiti Utara Malaysia. We have been successfully organized the previous conferences at West Hall ITB in 2006 and at Langkawi, Malaysia in 2010.

We hope that this 3rd scientific meeting forum could contribute to introduce and promote Technology and Operations Management especially in Indonesia, to open the way for possible collaboration between local and international academicians and practitioners to promote ITB, in particular SBM-ITB, as a world class university and as the leading higher institution in the field of technology and operations management.

On this occasion, we would like to say a big thank you to everyone who has helped in organizing this international conference and the preparation of proceedings. We also apologize for any shortcomings, both in the organizing of the conference and in the preparation of conference proceedings.

We look forward for your continuing supports and active participations in the next International Conference on Technology and Operations Management.