Experimental push/pull production planning and control system

We introduce an experimental push/ pull production planning and control software system which is designed as an alternative to a MRP-II system for mass manufacturing enterprises in China. It has the following distinguishing features: (1) putting the philosophy of JIT into the master production scheduling of MRP-II via the earliness/ tardiness production planning method; (2) controlling material input by push and processing/ assembly by pull; and (3) adjusting the parameters of the production line by the‘ suggestion for improvement of production line’ module. Simulation results have shown that the proposed system can achieve better planning and control performance than existing systems.     

A Simulation Study of Work-in-Process Inventory Drive Systems and their Effect on Operational Measurements

This simulation study compares three operational measures of performance through the exploration of three work-in-process (WIP) inventory drive systems and their associated inventory buffer characteristics. The three drive systems under study are a push, a pull and a hybrid push-pull system. While these systems have many aspects in common, their buffer management systems do not. The data analysis was based on information gathered from three computer-simulated flow shop assembly lines all operating in the same environment. Hypotheses concerning the operational performance measurements were established, independent variables were controlled and manipulated and a conclusion was drawn as to which system would afford the operation optimum results. While inventory has traditionally been considered and is currently being shown as an asset from an accounting point of view, it is obvious from the findings of this study, that excess WIP inventory, above the minimal requirements for production, may have a negative effect on the operational measurements evaluated.     

Integrating risk and performance management in quality management systems for the development of complex bespoke systems (CBSs)

Abstract

Risk and performance management are at the core of complex bespoke systems (CBSs). CBSs are developed to customer–specified requirements in terms of structure, functionality and conformance. This article examines how risk and performance management are integrated as essential systems in the successful development of projects across multi-organizational functions in complex bespoke system (CBS) organizations. The article argues for the development of a quality management system that consists of two sub-processes: quality control and quality development. Using three case studies from engineering companies, we provide evidence and insights of the way change control, quality development and quality performance are developed in innovating business solutions.     

The SAM Framework: Modeling the Effects of Management Factors on Human Behavior in Risk Analysis

Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.     

Assessing the effectiveness of a performance evaluation system in the public health care sector: some novel evidence from the Tuscany region experience

Since 80’s the introduction of New Public Management principles has promoted the use of performance measurement to drive a more efficient, effective and accountable public sector. The adoption of a sophisticated and comprehensive multidimensional performance measurement system, which looks beyond traditional financial measures, based on organization strategies, such as the balanced scorecard, has thus been suggested. This revolution in the public management came together with the devolution processes that involved most European public health systems. Set within this context, in the last decade, each of the twenty Italian regions developed its own management tools. Among others, the Tuscan performance evaluation system (PES) has been valued as a particularly innovative and comprehensive system. This paper reports the novel experience of the Tuscan PES; in particular, it measures PES effectiveness and discusses the critical factors that could have led to the PES success. Five are the critical success factors identified by researchers: the visual reporting system, the linkage between PES and CEO’s reward system, the public disclosure of data, the high level of employees and managers involvement into the entire process and the strong political commitment. All those factors run together to achieve better results; however, the process of development of the system plays a pivotal role. Scholars suggest the use of a constructive approach in order to gain effective changes in human organization. According to this stream of literature, this paper contributes by the novel experience of the Tuscan PES in addressing as a further fruitful application of the constructivist approach in healthcare.     

An approach to learning from both good and poor factory performance in a Kanban-based just-in-time production system

In a JIT manufacturing environment it may be desirable to learn from an archived history of data that contains information that reflects less than optimal factory performance. The purpose of this paper is to use rule induction to predict JIT factory performance from past data that reflects both poor (saturated or starved) and good (efficient) factory performance. Inductive learning techniques have previously been applied to JIT production systems (Markham et al. , Computers and Industrial Engineering, 34 , 717-726, 1998; Markham et al. , International Journal of Manufacturing Technology Management, 11 (4), 239-246, 2000), but these techniques were only applied to data sets that reflected a well-performing factory. This paper presents an approach based on inductive learning in a JIT manufacturing environment that (1) accurately classifies and predicts factory performance based on shop factors, and (2) identifies the important relationships between the shop factors that determine factory performance. An example application is presented in which the classification and regression tree (CART) technique is used to predict saturated, starved or efficient factory performance based on dynamic shop floor data. This means that the relationship between the variables that cause poor factory performance can be discovered and measures to assure efficient performance can then be taken.     

A proposed methodology for the prediction of mental workload, based on engineering system parameters

In the design of engineering systems, mental workload is one of the most important factors in the allocation of cognitive tasks. Current methods of task allocation have criteria that are defined in only general terms and are thus not very useful in aiding detailed decision-making in system design. Whilst there are many quantitative criteria available to determine the physical space in human-machine interaction, system designers really require an explicit model and specific criteria for the following identification of the mental workload imposed by the system; prediction of both human and system performance; evaluation of the alternatives of system design; and the design of system components. It is argued that the available methods of workload or performance are either too domain-dependent to apply to the design of other systems, or subject-dependent and thus do not reflect the objective workload imposed by the system. The presented research adopts a new approach to cognitive task analysis in dynamic decision-making systems. Based on the characteristics derived from task analysis, a general conceptual model of the prediction of mental workload in system design is proposed. In the new model, workload is represented by a set of system parameters—task arrival rate, task complexity, task uncertainty, and performance requirements—which are considered to be the main sources of workload. In this context, workload becomes an objective demand of engineering systems, independent of any subjective factors. Whether an individual or population is overloaded depends upon their workload threshold with respect to the specified task and environment. It is hoped that this new model, after both laboratory and industrial validation, could be used by system designers to predict the workload imposed on people by systems.     

The relative importance of planning and control systems in achieving good delivery performance

Amongst factors such as quick changeovers and workforce flexibility, managers in 533 UK manufacturing plants ranked a responsive planning and control system as the most important facilitator of good delivery performance on products made-to-order or assembled-to-order. The rankings indicate greater importance to companies in the Household and Engineering sectors than in Process and Electronics, where other factors are dominant. These results are combined with data such as customer lead times and item variety, to characterize and explain differences between the plants in these four sectors. Collectively the results indicate considerable differences in the production planning and control tasks. This implies that general statements on the importance of planning and control systems are inadequate. Practitioners need contextual information in order to ascertain when research is applicable to their circumstances.     

Determination of the optimal number of kanbans and kanban allocation in a FMS: A simulationbased study

A simulation-based study is presented to compare the performance of a set of kanban allocation rules in a flexible manufacturing system (FMS) operating in a pull mode. This paper also presents a simulation-based direct search approach to determine the optimal number of kanbans and their simultaneous allocation to different part types. This paper presents a realistic cost function that includes a penalty for failing to meet the demand on time, and a penalty for rescheduling delivery of materials from vendors. The model captures limited flexibility in the form of operational flexibility in a FMS. Future extensions to this study are discussed.     

MRP system performance under lumpy demand environments

Material requirements planning (MRP) systems are deemed to deal with master schedules with lumpy demand patterns better than any other production scheduling system. Past studies have advocated important advantages of using MRP systems. The objective of this paper is to look into the impact of patterns of demand lumpiness on the performance of MRP systems by a simulation study. Results show that there is an important threshold point in terms of degree of lumpiness at which MRP system performance starts to deteriorate in the operating conditions considered. If master production schedules (MPS) can be controlled by manufacturers, MRP users should exercise caution to introduce demand lumpiness in MPS to improve system performance. If not, MRP users should then examine the given lumpiness and choose an appropriate lot-sizing rule that has been shown to take advantage of the effect of demand lumpiness.     

Selection and implementation of a PPC system

There are many computer-aided production planning and control (PPC) systems available on the market which can provide a solution to the complex task of production planning and control. However, the question remains, how can a company find an optimal system from the vast amount of available systems? This article proposes that a company, having decided to buy one of the available systems, starts a project for selection and implementation of the PPC system.     

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.     

REDUTEX: a hybrid push–pull production system approach for reliable delivery time in knitting SMEs

The textile sector is composed of small and medium enterprises (SMEs) worldwide. Nowadays there is a shortage of technological knowledge in SMEs. Lead time is a critical indicator in any productive company organisation. The aim of this research was to provide an approach, called REDUTEX, based on theoretical concepts of lean and synchronous manufacturing in order to help to understand the behaviour of SMEs and to improve the manufacturing process by reducing the customer lead times. The integration of these philosophies is the basis of REDUTEX; a hybrid push–pull production system approach to knitting SMEs. With this approach, it is possible to obtain a process reliability when the restrictive resource capacity (RRC) is identified, optimised and protected. By synchronising all activities to the rhythm of RRC, through a continuous flow, it is possible to obtain high-impact results through a dual automated system and product quality, through a visual control. REDUTEX uses a push system from the RRC to the location of the supermarket, where accumulated inventory may be distributed in the internal assembly department and external family workshops, making a pull system. Subsequent re-assembly processes use a push system until the end of the product. The stages of REDUTEX are explicitly described and applied to real data, so that the staff of SMEs can easily understand the behaviour of the process and implement it. One of the advantages of REDUTEX is that it does not need highly trained staff. The research methodology was conducted as a case of study in twelve SMEs and validated and implemented in three textile companies of the southern area of the state of Guanajuato in Mexico, obtaining reliable delivery times and very promising results.     

An investigation of output flow control,bottleneck flow control and dynamic flow control mechanisms in various simple lines scenarios

Flow control mechanisms have been a topic of academic research for several years. With the growth of business-wide information systems such as enterprise resource planning and supply chain, better planning, scheduling and control of the business transformation process is required in order to achieve increased throughput, reduced inventories, shorter lead times and reduced tardiness. This research compares two new approaches to flow control, output flow control and bottleneck flow control to a real-time flow control system, dynamic flow control. Both output and bottleneck flow control mechanisms are much simpler to implement and manage than dynamic flow control in that they do not require continual feedback and rescheduling. Line characteristics, such as location of breakdowns with respect to the bottleneck, the location of the bottleneck when breakdowns occur, and the impact of variability of processing times on the performance measures (output, WIP level, lateness, and number of tardy jobs) for these three flow control mechanisms are compared. Both output and bottleneck flow control mechanisms perform favourably (particularly bottleneck) under different scenarios and warrant further study across a wider range of scenarios (mixed models, job shops, etc.).     

Integrated approach for optimizing quality control in international manufacturing networks

Abstract

This article aims at providing an integrated approach for optimizing quality control in International Manufacturing Networks (IMN) which can be characterized by consisting of numerous plants acting autonomously according to an individual target system. A key challenge is to ensure the overall process quality despite distributed value creation processes and differing target systems in dynamic environments. Hence, the developed approach allows for identifying potentials in the quality control strategy using a value stream-based method to visualize quality characteristics and procedures in the production process chain. Furthermore, the approach contains a framework for identifying possible improvement measures and a simulation-based evaluation concept to evaluate the effects of different measures with respect to individual target systems. The simulation combines elements of a discrete-event simulation in order to depict the value stream with agent-based modelling for realizing different target systems by considering distinctive plant roles. The article concludes with a case study of a globally operating automotive supplier to apply the approach. A forward research agenda is proposed that evaluates the approach in multiple cases, deriving patters across companies or industries.     

Implementing an RFID-based manufacturing process management system: Lessons learned and success factors

A growing number of organisations are using radio frequency identification (RFID) technology to improve their manufacturing processes. A case study approach is used to explore the development of an RFID-based manufacturing process management system in a garment factory in China. The results indicate that both technology push and need pull factors influence the garment factory's intention to adopt RFID technology. The technology push factors include relative advantage, compatibility, complexity, extendibility and the cost of the technology, whereas the need pull factors include competitor and customer pressure. We identify eight factors for the successful implementation of an RFID-based manufacturing process management system, namely, vendor selection, organisational motivation, cost/benefit evaluation, top management support, user involvement, the extent of progress supervision, staff competence and training, and policy, structure and operating process compatibility. This in-depth case study details the organisation's experience and identifies the challenges it faces and important issues in the development and implementation of the system. Implications for academics and practitioners are discussed.     

Application of TOC/OPT rules in a medium sized shop

Abstract

Abstract. Theory of constraints (TOC) and optimized production technology (OPT) are frequently presented as the better options for production control systems. Despite this enthusiasm, there is very little literature on how these principles can be implemented in practice without having to resort to the expensive proprietary software. In this paper we present a case study in which the OPT/TOC ideas were implemented without using the software. Management's major concern was reduction of work in process and increased delivery performance. It was decided to test whether the ideas of OPT/TOC were applicable in this environment and more importantly to which extent these two performance measures could be improved. The paper reports on the methodology used to test the OPT/TOC ideas in this shop and presents some early results of improvement, as well as some new problems which arose due to the new approach.     

Dynamic performance of a hybrid inventory system with a Kanban policy in remanufacturing process

In this paper we study a hybrid system with both manufacturing and remanufacturing. The inventory control strategy we use in the manufacturing loop is an automatic pipeline, inventory and order based production control system (APIOBPCS). In the remanufacturing loop we employ a Kanban policy to represent a typical pull system. The methodology adopted uses control theory and simulation. The aim of the research is to analyse the dynamic (as distinct from the static) performance of the specified hybrid system. Dynamics have implications on total costs in terms of inventory holding, capacity utilisation and customer service failures. We analyse the parameter settings to find preferred “nominal”, “fast” and “slow” values in terms of system dynamics performance criteria such as rise time, settling time and overshoot. Based on these parameter settings, we investigate the robustness of the system to changes in return yield and the manufacturing/remanufacturing lead time. Our results clearly show that the system is robust with respect to the system dynamics performance and the remanufacturing process can help to improve system dynamics performance. Thus, the perceived benefits of remanufacturing of products, both environmentally and economically, as quoted in the literature are found not to be detrimental to system dynamics performance when a Kanban policy is used to control the remanufacturing process.     

Improving control through effective performance measurement in SMEs

Research has demonstrated that the use of performance measures in SMEs (small to medium sized enterprises) is limited. Financial measures, which are required for examination by external stakeholders, are generally well developed. However, operational measures are typically ad hoc and lack formal structure. A structured approach to measuring perform ance in SMEs should improve strategic control. Current approaches, however, have proved inadequate for the specific requirements of the SME sector. A new process is presented for developing effective performance measurement in SMEs, which is tested through a case study. The aim of the process is to develop measures that drive operational performance towards the achievement of strategic objectives. The results of the case study demonstrate the potential of the process for improving strategic control and stimulating continuous improvement in SMEs.