The role of social and intellectual capital in achieving competitive advantage through enterprise resource planning (ERP) systems

Enterprise resource planning (ERP) software merges a firm's data, information flows and business processes into a single package. Vendors argue that ERP provides an extremely useful strategic resource to enhance competitiveness and make it possible for a firm to leverage its other resources more effectively and efficiently. In addition, they allege that ERP encourages a system-wide perspective that is a basis for collaboration and a systems orientation. However, an examination of ERP systems using criteria established in research on resource-based views of the firm and chaos/complexity theory indicates that these claims are overstated. Observation suggests that even if ERP is necessary to coordinate complicated, multifaceted operations, it is far from sufficient to promote a strong competitive position over the long term. Moreover, ERP systems fit best within mechanistic, clockwork organizations dominated by routine, highly programmed technologies and operations, yet it is the non-routine learning and change processes found in complex, self-organizing systems that enable firms to create distinctive competitive advantages from ERP outputs. ERP makes possible deep changes in relationships, culture, and behaviors that can be crucial sources of advantage in the knowledge economy, but the structures and cultures most able to achieve this level of change are a poor fit with ERP requirements. To reconcile this paradox, we propose a dual-core, loosely coupled organization that views ERP as an enabling technology to build and augment social and intellectual capital, rather than as an information technology (IT) solution for organizational inefficiencies. Propositions for using ERP as a foundation for social and intellectual capital formation are introduced. Implications for research and practice are discussed.     

Distributed manufacturing support systems: the integration of distributed group support systems with manufacturing support systems

Current Manufacturing Support Systems (MSS), such as Computer-aided Manufacturing (CAM) Systems, Computer-aided Design (CAD) Systems, Computer Integrated Manufacturing (CIM) Systems, Material Resource Planning (MRP) Systems, and Manufacturing Accounting Control (MAC) Systems, are mostly independent systems that are operated in limited decision spaces, provide mainly formal and quantitative information, and thus pursue a goal of local optimization. To assist modern manufacturing in meeting the needs for integration, communication, collaboration, and decision making, we introduce the concept of integrating MSS with Distributed Group Support System (DGSS) into a Distributed Manufacturing Support System (DMSS). A rigorous system design approach is taken to model the manufacturing information requirements from a global perspective and pattern decision making processes within the structural (organizational design) and infrastructural (information system design) elements of manufacturing. The result is a conceptual DMSS design that provides an intelligent interface, accommodates incremental manufacturing integration, offers controllable message exchange facilities, and allows configurable communication networks.     

Automated simulation modelling and analysis for manufacturing systems

Simulation is extensively used as a basis for the analysis and design of manufacturing systems. It has been steadily increasing in popularity due to the simplicity and ease of model understanding even by the non-simulationist. The popularity of simulation is also due to recent developments of easy-to-use simulation software. Simulation generators represent a significant trend in this direction. More recent developments include simulation expert systems both from the viewpoint of modelling and also statistical output analysis. The work that has been explained herewith is based on one such simulation generator that has been developed at the Center for Manufacturing Productivity and Technology Transfer at Rensselaer Polytechnic Institute. This system, RENSAM (RENssclaer Simulator for Automated Manufacturing) is an adaptive simulation generator and has an underlying structure that represents a FMS. The research that has been accomplished is the result of the constant efforts that are being undertaken to make RENSAM a complete decision making tool. In order to achieve what is envisioned, output analysis, optimization and sensitivity analysis routines have been added to the generic simulation and intelligent front end (IFE), The output analysis routine determines the experimental conditions under which the simulation is executed. The optimization routine searches for the optimal values for the parameters of interest and then sensitivity analysis is used to examine the relationship among various parameters. The sensitivity analysis that is presented has been developed taking into account various methodologies in this field.     

A heterarchical generic discrete manufacturing simulation model and its application in a world class manufacturing environment

Current factory design and evaluation is very primitive. Factory components are designed in many cases independently. Product and process design are not well integrated. An encompassing framework is needed for iterating through a series of total factory designs, searching for optimal performance. In addition, a vehicle is needed for predicting the performance of a proposed advanced manufacturing system, so that engineers may have a sound means for evaluating such proposals. A heterarchical discrete manufacturing SIMNET II simulation model (SIMCELLS) was developed as a comprehensive methodology for designing and evaluating discrete manufacturing systems. SIMCELLS allows manufacturing systems engineers to experiment with alternative system structures and control strategies while seeking that combination of design features that will produce the desired overall system performance. The model in combination with a modernization programme is enabling a firm to successfully manufacture and sell trucks meeting international standards. The SIMNET II model     

A standard-based business repository for on-demand manufacturing execution systems

In manufacturing execution system (MES) projects, knowledge is heterogeneous and is applied partially in each software package. Consistency is therefore critical. Some standard business reference models exist, such as the IEC/ISO 62264 standard for MESs (also known as ISA S95), or the Supply Chain Operations Reference model for supply chain planning (SCP) and execution (SCE). These reference models have some overlaps. For example, traceability is part of both MES and SCE packages. A consortium of manufacturing software editors for industry has launched an ‘MES on demand’ platform using services from different packages. This paper presents the enriched business repository model built to facilitate business heterogeneity. It is used to align different business repositories (B–B alignment) and different business and software packages (B–S alignment). It likewise serves to align customer requirements with the repository (B–C alignment). The consortium platform is then ‘S95 compliant’ when knowledge supported by the different actors is included.     

Simulation-based performance assessment of master planning approaches in semiconductor manufacturing

Semiconductor manufacturing is confronted with a large number of products whose mix is changing over time, heterogeneous fabrication processes, re-entrant flows of material, and different sources of environmental and system uncertainty. In this context, the mid-term production planning approach, i.e., master planning, typically does not capture the entire complexity of the shop-floor. It deals with an aggregated representation of the production system. There is a need for evaluating the planning algorithm in use while taking the execution level into account. Therefore, we introduce in this paper a simulation-based framework that allows for modeling the behavior of the market demand and the production system. An appropriate performance assessment methodology is proposed. The performance of two heuristic approaches for master planning in semiconductor manufacturing, a genetic algorithm and a rule-based assignment procedure, is evaluated within a rolling horizon setting while considering demand and execution uncertainty. A reduced discrete-event simulation model is used to mimic a one-stage network of wafer fabrication facilities. The results of simulation experiments are discussed.     

Integration of the information systems in the production process: a case study

This paper evaluates the execution of an ERP – enterprise resource planning in a production process. The changes that were made to processes to make them compatible with ERP modules and adaptations that were required by the ERP implementation are presented. The presented study is different from the normal patterns of a vertical implementation, since its application is not direct. In order to use the standard modules of the ERP system, the internal processes were embellished and the data collection steps were integrated into the production process (production orders, inventory, production, daily consumption, daily output). The case study shows that the ERP implementation caused an improvement of the processes in the areas adjacent to production (purchasing, logistics, distribution, supply and sales). In conclusion, this paper presents the main advantages and disadvantages of the ERP system implementation, as well as some considerations and recommendations for the future ERP implementations.     

Simulation optimization through direct search for multi-objective manufacturing systems

Simulation modelling has been one of the most widely used techniques for analysing complex manufacturing systems. In this paper, we propose a direct search algorithm expanded from the Hooke-Jecves pattern search to systematically and efficiently locate satisfactory solutions for multi-objective simulation models. The user-specified goals can be precise and/or fuzzy. Heuristic rules stemming from the simulation result of resource statistics are incorporated into the Hooke-Jeeves pattern search. The proposed heuristic rules make the search procedure effective regardless of different initial points and various bounded ranges of decision variables. Experimental results show that the proposed approach is suitable for analysing complex manufacturing systems, in which multiple objectives and multiple decision variables are encountered.     

Hierarchical model to design manufacturing systems applied to a metal-mechanic company

This paper describes the application of a model to design and manage the manufacturing process through an integrated system, using a Hierarchical methodology-by means of different aggregation and disaggregation stages with an appropriate time horizon. The hierarchical model obtained allows interfacing between the master schedule and the schedule of the orders. At each level of the hierarchical model some decisions have to be made in order to design the manufacturing system, but having a model that also takes into consideration the management of the system. To do this it is necessary to use aggregated information concerned with the level at which decisions are made. It is obtained from the database, which contains the information at the highest level of aggregation. This model has been applied to a metal mechanic company, that makes final products such as car washers, etc. The benefits of this approach for the company are addressed in this paper.     

Freezing the master production schedule in multilevel material requirements planning systems under deterministic demand

This paper extends the studies by Sridharan, Berry, and Udayabhanu from single-level MPS systems to multilevel material requirements planning (MRP) systems, and examines the impact of product structure, lot-sizing rules and cost parameters upon the selection of MPS freezing parameters under deterministic demand. A model is built to simulate the master production scheduling and material requirements planning operations in a make-to-order environment. The results show that all the MPS freezing parameters studied have a significant impact upon total inventory costs and schedule instability in multilevel MRP systems. First, the order-based freezing method is preferable to the period-based method. Secondly, the study finds that increasing the freezing proportion reduces both total inventory costs and schedule instability. This finding contradicts the finding by Sridharan et al. in single-level systems. Thirdly, the study finds that a higher replanning periodicity results in both lower total inventory cost and lower schedule instability. The study also indicates that the product structure and lot-sizing rules do not significantly influence the selection of MPS freezing parameters in a practical sense under most situations. However, the cost parameter seems to significantly influence the selection of replanning periodicity.     

Positioning a company in enterprise collaborations: Vertical integration and make-or-buy decisions

During any strategic development, a firm has to position itself in its supply chain. The decision as to how many activities in the chain to occupy is known as vertical integration and is termed as make-or-buy when an individual activity is considered. Because of its very nature, this category of decisions may be made only within the framework of an extended enterprise. To support such a decision-making process, a model is described that defines all key elements needed to make such critical decisions. More precisely, a set of rules must present all items which have to be defined and valued, and the relationships between them, in order to conclude if an activity must be processed internally (Make) or supplied externally (Buy). This paper details such a hierarchy of rules.     

A review of hierarchical production planning and its applicability for modern manufacturing

The hierarchical production planning (HPP) paradigm has become an accepted planning and control strategy for many medium-to-large manufacturing situations. While the paradigm appears intuitively obvious and appropriate for many factories, there are a number of modern manufacturing situations where the application of the HPP approach may not be appropriate. By understanding the fundamental principles and concepts inherent in the HPP approach, it is possible to identify situations suitable for HPP with little or no adaptation, and situations where HPP must be extensively modified before use. A poor understanding of HPP     

企业车间系统结构与工艺复杂性多维度评价

提出了信息力、能和结构复杂性信息量度量的基本概念、定义、基本原理和数学模型;建立了企业生产系统结构复杂性评价的新尺度;提出了评价方法和系统结构的简约化、复杂性减少原理;并应用此理论与方法对井工企业掘进工作面系统结构复杂性评价进行了实证研究.     

A simulation testing and analysis of aggregate production planning strategies

In this study, a hybrid discrete event simulation (DES) and system dynamics (SD) methodology is applied to model and simulate aggregate production planning (APP) problem for the first time. DES is used to simulate operational-level and shop-floor activities incorporated into APP and estimate critical time-based control parameters used in SD model of APP and SD is used to simulate APP as a collection of aggregate-level strategic decisions. The main objective of this study is to determine and analyse the effectiveness of APP strategies regarding the Total Profit criterion by developing a hybrid DES–SD simulation model for APP in a real-world manufacturing company. The simulation results demonstrated that the priority of APP strategies with regards to Total Profit criterion is: (1) the pure chase strategy, (2) the modified chase strategy, (3) the pure level strategy, (4) the modified level strategy, (5) the mixed strategy and (6) the demand management strategy, respectively. The APP system is first simulated under mixed strategy (basic scenario) conditions to include all APP capacity and demand options in constructed SD simulation model to show a comprehensive view of APP components and their interdependent interactions. Then, the obtained results will be used as Total Profit measure to compare with system's performance under some experimental scenarios applying different APP strategies.     

Improving supply chain responsiveness through Advanced Manufacturing Technology: the mediating role of internal and external integration

Abstract

Responsiveness is one of the key performance factors that firms need to face up to the challenges posed by today’s markets. Many manufacturing firms are investing in advanced manufacturing technology (AMT) with a view to improving competitiveness. However, empirical evidence shows that investments in AMT alone do not lead to improvements in performance. In this study, a model that links AMT implementation and responsiveness through internal integration and external integration is proposed. A sample of 441 Spanish industrial companies was used to test the model through structural equation modelling. The findings highlight that internal integration needs to be supplemented with external integration in order to ensure that the implementation of AMT will result in improved responsiveness. Supply chain managers should focus on integration within the supply chain – firstly internal and later external – to obtain returns on investments in AMT in the form of improved flexibility and more reliable and faster deliveries.     

On the integration of production,inventory and trade-credit policies

The primary objective of this paper is to highlight the need for the integration of procurement, production and marketing strategies. This is accomplished through the development of a model for a small firm, where the objective is the maximization of the present value of profits within an infinite horizon framework Other features include a JIT-like procurement system, a continuous production situation and a combination of cash discounts and credit period to stimulate sales. A numerical example is presented to illustrate the main features of the study.     

Integration of process planning and production planning and control in cellular manufacturing

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.     

Computational complexity of algorithms for MRP and JIT production planning problems in enterprise resource planning systems

An enterprise resource planning system (ERP) is the information backbone of many manufacturing companies. At the core of ERP is a conventional material requirements planning (MRP) production planning system or a variation of MRP when just-in-time (JIT) principles are used in manufacturing. MRP and JIT both organize production planning into a hierarchy of long-, medium- and short-range problems. In all there are eight different problems. Some are common to MRP and JIT, others are specialized for a particular system. This paper analyses the computational requirements of these problems. This is important for ERP because it plans for large numbers of products (e.g. 50 000 products at 3M Company and 44 000 products at States Industries in Oregon) at large numbers of locations (e.g. 82 locations in 21 countries for Visteon Automotive Systems of Michigan and 19 locations at Boeing). We show that adequate algorithms exist for some problems, but better algorithms are needed for other problems if ERP is to provide useful production plans.     

Implementation of S-DBR in four manufacturing SMEs: a research case study

Production planning and control systems (PPCs) are tools that have a major effect on the performance of manufacturing companies. An inappropriate determination of the applicability of PPCs could seriously jeopardise the ability to achieve competitive priorities. This mistake can be expensive for any company, but proper implementation is particularly critical for small and medium enterprises (SMEs), which are characterised by limited access to financial resources. Simplified Drum–Buffer–Rope (S-DBR) is a PPC control approach that is characterised by minimum detail in the planning stage and a primary emphasis on the control of execution. Therefore, this approach is a suitable choice for the highly variable context of SMEs. This study aims to explore the practical issues related to S-DBR implementation in four Ecuadorian SMEs through case study research. The case analysis within this study first identifies the choices made in the implementation process design within the four companies according to process and product characteristics. We then conduct a cross-case analysis to explore the effects of the S-DBR implementation process designs on a group of performance measures. Our research findings provide new insights into the S-DBR implementation process in the context of SMEs, and the effects of this approach on performance measures.     

Changes in production control required for untended operation of a flexible manufacturing cell

This article examines and improves the production control system of a firm that wants to operate its flexible manufacturing cell (FMC) in an untended third shift. The FMC consists of a machining centre, a pallet storage, a rail-guided transport vehicle for pallets and a clamping/unclamping station. The current production control system of the firm shows several deficiencies with respect to operating the FMC efficiently. This article proposes changes in the current production control hierarchy and introduces some new methods to solve major production control problems. The study illustrates the interaction between quantitative tools, organisational decisions and behavioural considerations. The approaches are general and can be used in other environments.