Does Management Matter? Evidence from India

A long-standing question in social science is to what extent differences in management cause differences in firm performance. To investigate this we ran a management field experiment on large Indian textile firms. We provided free consulting on modern management practices to a randomly chosen set of treatment plants and compared their performance to the control plants. We find that adopting these management practices had three main effects. First, it raised average productivity by 11% through improved quality and efficiency and reduced inventory. Second, it increased decentralization of decision making, as better information flow enabled owners to delegate more decisions to middle managers. Third, it increased the use of computers, necessitated by the data collection and analysis involved in modern management. Since these practices were profitable this raises the question of why firms had not adopted these before. Our results suggest that informational barriers were a primary factor in explaining this lack of adoption. Modern management is a technology that diffuses slowly between firms, with many Indian firms initially unaware of its existence or impact. Since competition was limited by constraints on firm entry and growth, badly managed firms were not rapidly driven from the market.management, organization, IT, productivity and India

Does Management Matter? Evidence From India

A long-standing question in social science is to what extent differences in management cause differences in firm performance. To investigate this we ran a management field experiment on large Indian textile firms. We provided free consulting on modern management practices to a randomly chosen set of treatment plants and compared their performance to the control plants. We find that adopting these management practices had three main effects. First, it raised average productivity by 11% through improved quality and efficiency and reduced inventory. Second, it increased decentralization of decision making, as better information flow enabled owners to delegate more decisions to middle managers. Third, it increased the use of computers, necessitated by the data collection and analysis involved in modern management. Since these practices were profitable this raises the question of why firms had not adopted these before. Our results suggest that informational barriers were a primary factor in explaining this lack of adoption. Modern management is a technology that diffuses slowly between firms, with many Indian firms initially unaware of its existence or impact. Since competition was limited by constraints on firm entry and growth, badly managed firms were not rapidly driven from the market.management, organization, IT, productivity and India

Does management matter ? evidence from India

A long-standing question in social science is to what extent differences in management cause differences in firm performance. To investigate this, the authors ran a management field experiment on large Indian textile firms, providing free consulting on modern management practices to a randomly chosen set of treatment plants and compared their performance to the control plants. They find that adopting these management practices had three main effects. First, it raised average productivity by 11 percent through improved quality and efficiency and reduced inventory. Second, it increased decentralization of decision making, as better information flow enabled owners to delegate more decisions to middle managers. Third, it increased the use of computers, necessitated by the data collection and analysis involved in modern management. Since these practices were profitable this raises the question of why firms had not adopted these before. Their results suggest that informational barriers were a primary factor in explaining this lack of adoption. Modern management is a technology that diffuses slowly between firms, with many Indian firms initially unaware of its existence or impact. Since competition was limited by constraints on firm entry and growth, badly managed firms were not rapidly driven from the market.Labor Policies,E-Business,Agricultural Knowledge&Information Systems,Rural Development Knowledge&Information Systems,Labor Markets

State of the art in simulation-based optimisation for maintenance systems

Recently, more attention has been directed towards improving and optimising maintenance in manufacturing systems using simulation. This paper aims to report the state of the art in simulation-based optimisation of maintenance by systematically classifying the published literature and outlining main trends in modelling and optimising maintenance systems. The authors investigate application areas and published real case studies as well as researched maintenance strategies and policies. Much of the research in this area is focusing on preventive maintenance and optimising preventive maintenance frequency that will lead to the minimum cost. Discrete event simulation was the most reported technique to model maintenance systems whereas modern optimisation methods such as Genetic Algorithms was the most reported optimisation method in the literature. On this basis, the paper identifies the current gaps and discusses future prospects. Further research can be done to develop a framework that guides the experimenting process with different maintenance strategies and policies. More real case studies can be conducted on multi-objective optimisation and condition based maintenance especially in a production context

Opportunistic Preventive Maintenance Scheduling Based on Theory of Constraints

Abstract In recent years, to improve system reliability and economy, machine maintenance strategies have been paid more and more intention by researchers. This paper aims to integrate the concept of theory of constraints (TOC) into multi-machine opportunistic maintenance policy. Based on the preventive maintenance algorithm, an improved model containing bottleneck strategy which influences opportunistic maintenance has been developed. By maximizing total cost saving, an optimal maintenance schedule of all machines in a series product line can be obtained. The results of a case study show that this model is valid for planning a comprehensive optimal maintenance schedule. Furthermore, by comparing with other models, this model has been proven to be more effectively especially in series product lines with bottleneck

Maintenance Performance Optimization for Critical Subsystems in Cement Pre-Grinding Section: A Case Study Approach

This paper aims to develop a simulation-based framework to identify critical equipment, critical maintenance and operational factors (e.g., maintenance actions, spare sourcing lead times and fill rate) affecting plant performance (availability and maintenance cost). The study develops a framework that utilizes empirical maintenance data. Pareto analysis is employed to identify critical subsystems, while expert input is incorporated to derive model variables. A full factorial Design of Experiment (DOE) is employed to establish the variables with significant main and interaction effects on the plant availability and maintenance cost. The framework is applied to a real case study of a cement-manufacturing firm, where a simula- tion model is developed based on the empirical maintenance and operational data while considering the availability and maintenance cost as the performance measures. Simulation results highlight the bucket elevator as the critical subsystem. At the same time, spare parts importation probability, among other parameters like the preventive maintenance interval and utilization of adjust maintenance action, significantly affects the performance (availability and maintenance cost) as main and interaction effects. The research was applied to only one case study, in this case, a cement grinding plant. The study provides a pragmatic reference model framework to practitioners that enhances maintenance decision-making by identifying critical equipment, maintenance and operational parameters and disclosing their effect (main and interaction) on the plant performance (availability and maintenance cost). This study is one of the first to (i) investigate the maintenance and operational factors’ main and interac- tion effects on maintenance cost and (ii) integrate the spare parts importation probability as a factor affecting plant performance. The developed framework assists in determining critical systems to be optimized, considers various maintenance strategies simultaneously, the stochasticity of spare parts availability and replenishment and ultimately discovers the interactions for decision support

Maintenance modelling of a major hospital complex

By its nature, building maintenance requires an ability to respond to a demand that is random in time, random in nature and random in location. This in turn creates complex operational and logistical problems for management, specially if the property complex is large.The objective of this research is to assess the scope for and effectiveness of quantitative modelling, and the prediction of the outcome of alternative management action (policy), to assist in the management of building maintenance complexes of the size of a hospital. Both building and engineering equipments are encompassed within the study as appropriate. The research issues are split into three related phases; a demand study; a defect reduction study; and a maintenance management model. 1- The maintenance demand study: Based upon general statistics obtained, attempts have been made to identify and quantify both the major problems areas (in terms of cost and frequency of maintenance activities), and the nature and cause of the demand for maintenance. They have revealed no coherent picture in that the demand from wards and buildings seems independent of the patient throughput andthe age of buildings. The demand for maintenance, for the main trades involved, has been estimated and used in the simulation models mentioned in below. 2- Demand reduction model: Accepting the current demand situation for maintenance, it was proposed to identify what is the cause of the demand and what possible actions could reduce the demand: Possibly through design modification, changes in materials used, change in practice of service/building user, development of Preventive Maintenance 'PM' or inspection system for component. Despite considerable effort, it proved not possible to progress this aspect of the study and the reasons are discussed. 3- Maintenance management models: Simulation models to the maintenance activities within the hospital has been developed using, Extended Control and Simulation Language, ECSLPLUS, to model the maintenance policies, and assessing any changes in operating procedures. The advantage of modelling is that the magnitude and nature of changes can be assessed and contemplated prior to any actual change in operating procedures. This is generally recognised as being most valuable. For specific problems and areas of operation identified, development of specific methods of deployments have been attempted. For instance, 'recieving one job at a time'; 'recieving a batch of jobs at a time'; and 'delaying non-urgent jobs and grouping them in time'. A number of maintenance management policies have been assessed using the above models, these are: 'Previewing' and 'not previewing' most of the defects before repair to identify the required resources; 'employing extra part-timetradesmen during the busy days'; 'working 7 days instead of 5 days a week'; 'no sickness policy'; and 'employing multi-skilled tradesmen option'. These models should be capable of indicating to management the gains and consequances, in terms of measures of interest to them such as the workforce and manhours required to meet the demand for maintenance per trade, changing operating practice, customs and timescales. That is, their decision variables

Interval Preventive Maintenance Dengan Dasar Keandalan

Maintenance merupakan lini support process dalam model bisnis CIMOSA. Meskipun termasuk dalam support process namun dengan penanganan yang tepat akan memberi dampak penghematan yang besar. Studi kasus dalam penelitian ini yakni Machine Direct Order (MDO) pada lini produksi BOPP 6. Penelitian ini memberikan dampak untuk memudahkan aktivitas maintenance yang tepat dengan penanganan hanya terkonsentrasi pada komponen kritis saja. PT Trias Sentosa belum melakukan Preventive Maintenance dengan dasar perhitungan keandalan, hal inilah yang mendasari penelitian ini untuk dilakukan. Berdasarkan data kerusakan dan pengolahan penentuan kritis, maka didapatkan bahwa komponen Nip Roll MDO 6 dan 3 memiliki karakteristik sesuai distribusi yang telah diolah dengan software Weibull++6 yakni Weibull 2 Parameter, hasil MTTF dan MTTR menjadi dasar acuan dalam pembuatan jadwal preventive maintenance rekomendasi. Jadwal rekomendasi awal memberikan nilai opportunity cost sebesar Rp 8.588.646.566,40 dan dengan integrasi time to repair kondisi eksisting maka opportunity cost dapat diperkecil menjadi Rp 1.717.729.313,28. Dasar penentuan integrasi ini yakni dari pembandingan dampak availability terhadap opportunity cost pada original MTTF dan interval perawatan eksisting. Opportunity cost paling minimum yakni apabila jadwal rekomendasi awal diintegrasikan dengan nilai time to repair berdasarkan kondisi eksisting, hal inilah yang menjadi dasar dalam pembuatan jadwal skenario terbaru yang memiliki dampak opportunity cost terkecil. ========================================================================================================= Maintenance is a line of support in the business model CIMOSA process. Although included in the support process, but with the right treatment it will impact big savings. The case studies in this research namely Machine Direct Order (MDO) in BOPP production line 6. This study gives effect to facilitate maintenance activities appropriate to handling only concentrated on critical components only. Preventive Maintenance in PT Trias Sentosa not done on the basis of calculation of reliability, it is the underlying this research to be done. Based on data from damage and critical determination processing, it was found that the component Nip Roll MDO 6 and 3 have characteristics consistent distribution that has been processed with the software Weibull ++ 6 is Weibull 2 Parameter, MTTF and MTTR results are the basis in making preventive maintenance schedule recommendations. Schedule initial recommendations give the opportunity cost of Rp 8,588,646,566.40 and the integration time to repair the existing condition then the opportunity cost can be reduced to Rp 1,717,729,313.28. The basis for determining the integration of benchmarking is the impact of the availability on the opportunity cost with original MTTF and existing maintenance (time to repair) intervals. The most minimum opportunity cost is when the initial recommendation schedule is integrated with the value of time to repair based on existing condition, thus themost minimum impact of opportunity cost will be achieved