scholarly journals Managing Manufacturing Complexity Drivers on Performance – An Initial Study

2018 ◽  
Vol 2 (1) ◽  
pp. 45-50
Author(s):  
Keyword(s):  
Strong Correlation ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Initial Study ◽  
Efficient Production ◽  
Product Management ◽  
Nonlinear Behaviour ◽  
Manufacturing Companies ◽  
Manufacturing Performance ◽  
Manufacturing Productivity

Manufacturing systems, in pursuit of cost, time and flexibility optimisation are becoming more and more complex, exhibiting a dynamic and nonlinear behaviour. Unpredictability is a distinct characteristic of such behaviour and effects production planning significantly. Complexity continues to be a challenge in manufacturing systems, resulting in ever-inflating costs, operational issues and increased lead times to product realisation. This challenge must be met with appropriate decision-making by manufacturing companies to secure competitive advantage without compromising sustainability. Assessing complexity realises the reduction and management of complexity sources which contribute to lowering associated engineering costs and time, improves productivity and increases profitability. Therefore, this study was undertaken to investigate the priority level and current achievement of manufacturing performance in Malaysia’s manufacturing industry and the complexity drivers on manufacturing productivity performance. The results showed that Malaysia’s manufacturing industry prioritised product quality and they managed achieved a good on-time delivery performance. However, for other manufacturing performance, there was a difference where the current achievement of manufacturing performances in Malaysia’s manufacturing industry is slightly lower than the priority given to them. The strong correlation of significant value for priority status was observed between efficient production levelling (finished goods) and finish product management while the strong correlation of significant value for current achievement was minimised the number of workstation and factory transportation system. This indicates that complexity drivers have an impact towards manufacturing performance. Consequently, it is necessary to identify complexity drivers to achieve well manufacturing performance.

Differences in the impact of AMO bundles of line managers and frontline workers on the performance of manufacturing firms

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alberto Bayo-Moriones ◽  
Alejandro Bello-Pindado
Keyword(s):  
Manufacturing Industry ◽  
Manufacturing Firms ◽  
Manufacturing Companies ◽  
Linear Regression Models ◽  
Line Managers ◽  
Content Type ◽  
Frontline Workers ◽  
Hrm Practices ◽  
Manufacturing Performance ◽  
The Impact

PurposeThe purpose of this paper is to analyse the impact on manufacturing performance of human resource management (HRM) practices across two job levels within manufacturing firms in Argentina and Uruguay: that of line managers and frontline workers. HRM practices are categorised into three bundles defined by the AMO theoretical framework: ability, motivation and opportunity.Design/methodology/approachThe article uses data from a survey to 301 manufacturing plants in Uruguay and Argentina. Given the characteristics of the dependent variable, linear regression models have been estimated in order to test the hypotheses.FindingsThe results show that the ability and opportunity bundles for line managers are positively associated with manufacturing performance. However, only the motivation bundle affects manufacturing performance for frontline workers.Research limitations/implicationsThe main limitations are the use of cross-sectional data, the focus on two specific countries and the analysis of two employee categories that are not completely homogenous. The paper extends the contingency perspective in HRM by examining the relevance of job level as a contingent factor in the HRM-performance relationship in the manufacturing industry.Practical implicationsThe results suggest that manufacturing companies should target HR investments more towards line managers than to frontline employees. More specifically, they should concentrate efforts on the ability and opportunity bundles.Originality/valueThe article contributes to the very limited empirical evidence on the impact of HRM differentiation on firm performance by analysing sub-dimensions in a context not previously analysed.

Managing Complexity in Manufacturing Changeovers: A Sustainable Manufacturing-Oriented Approach and the Application Case Study

2016 ◽  
Author(s):  
Khalid Mustafa ◽  
Kai Cheng
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Business Models ◽  
Sustainable Manufacturing ◽  
Lead Times ◽  
Manufacturing Companies ◽  
Factors Affecting ◽  
Manufacturing Complexity ◽  
Oriented Approach

Increasing manufacturing complexity continues to be one of the most significant challenges facing the manufacturing industry today. Due to these rapid changes in manufacturing systems, one of the most important factors affecting production is recognized as the frequent production setup or changeovers, consequently affecting the overall production lead times and competitiveness of the company. Developing responsive production setup and process capability is increasingly important as product ranges and varieties in manufacturing companies are growing rapidly and, at the same time, production business models are operating more towards being customer-oriented. Furthermore, although different conventional methods have been used to manage complexity in production changeovers, sustainability and competitiveness development in a manufacturing company needs to be scientifically addressed by managing manufacturing complexity. In this paper, a sustainable manufacturing-oriented approach is presented in mind of managing manufacturing changeover complexities. A case study is carried out specifically concerning changeover complexity in a pharmaceutical company, aiming at minimizing complexities in production changeover and waste, increasing plant flexibility and productivity, and ultimately the sustainable competitiveness of the company in managing manufacturing changes.

Comparison of Different Scenarios Using Computer Simulation to Improve the Manufacturing System Productivity: Case Study

2013 ◽  
Vol 845 ◽  
pp. 770-774 ◽  
Author(s):  
Seyed Mojib Zahraee ◽  
Milad Hatami ◽  
J.M. Rohani ◽  
H. Mihanzadeh ◽  
Mohammadreza Haghighi
Keyword(s):  
Computer Simulation ◽  
Production Line ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Manufacturing System ◽  
Waiting Times ◽  
Manufacturing Companies ◽  
System Productivity ◽  
High Resource

In the manufacturing industry, managers and engineers are seeking to find methods in order to eliminate the common problems in manufacturing systems such as bottlenecks and waiting times. This is because that all of these kinds of problems impose extra cost to the companies. In addition, manufacturing companies are striving to sustain their competitiveness by improving productivity, efficiency and quality of manufacturing industry for instance high throughput and high resource utilization. The paper concentrates on the application of computer simulation to analysis manufacturing system in order to improve the productivity. Therefore, this study introduces a color manufacturing line as a case study and the basic application of arena 13.9 software. The goal of this paper is to improve the productivity and efficiency of the production line by using computer simulation. To achieve this goal, first the basic model of the current situation of production line was simulated. Second, three different alternatives were simulated and modified to find the best scenario based on the maximum productivity and minimum total cost.

scholarly journals Applying the PDCA Cycle to Reduce the Defects in the Manufacturing Industry. A Case Study

2018 ◽  
Author(s):  
Arturo Realyvásquez-Vargas ◽  
Karina Cecilia Arredondo-Soto ◽  
Teresa Carrillo ◽  
Gustavo Ravelo
Keyword(s):  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Welding Process ◽  
Manufacturing Companies ◽  
Delivery Times ◽  
Pdca Cycle ◽  
Increasing Demand ◽  
Quality Of Products

Defects are considered one of the wastes in manufacturing systems that negatively affect the delivery times, cost and quality of products leading to manufacturing companies facing a critical situation with the customers and to not comply with the IPC-A-610E standard for the acceptability of electronic components. This is the case is a manufacturing company located in Tijuana, Mexico. Due to an increasing demand on the products manufactured by this company, several defects have been detected in the welding process of electronic boards, as well as in the components named Thru-Holes. It is for this reason that this paper presents a lean manufacturing application case study. The objective of this research is to reduce at least 20% the defects generated during the welding process. In addition, it is intended to increase 20% the capacity of 3 double production lines where electronic boards are processed. As method, the PDCA cycle, is applied. The Pareto charts and the flowchart are used as support tools. As results, defects decreased 65%, 79% and 77% in three analyzed product models. As conclusion, the PDCA cycle, the Pareto charts, and the flowchart are excellent quality tools that help decrease the number of defective components.

scholarly journals Implementasi Algoritma Wagner-Within pada Manajemen Inventori di PT X

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Puspandam Katias ◽  
Achmad Affandi
Keyword(s):  
Production System ◽  
Manufacturing Industry ◽  
Raw Materials ◽  
Raw Material ◽  
Efficient Production ◽  
Manufacturing Companies ◽  
Inventory Cost ◽  
Qualitative Descriptive ◽  
Total Inventory ◽  
Supporting Material

The increasing competition in the manufacturing industry caused increasing inconsumer demand of the quality and quantity of a good product. Therefore, manufacturing companies must have reliable services, policies and product qualities to satisfy its customers. So it needs to be supported by efficient production system and inventory system. To able to create an efficient production system then need a good raw material inventory planning. This research aims to compere how efficiently in planning raw materials inventory between Wagner-Within Algorithm with the actual concept that applied to PT X, Sidoarjo. The methodology of this research is qualitative descriptive research. The findings this research is engaged in packaging (woven bag and jumbo bag) with main raw materials such as plastic ore and supporting material in inner, thread, additive, and pigment. Based on the result of the analysis is known that the actual concept of the company gives the total inventory cost IDR 3.151.000.000 with the frequency of ordering 12 times while WagnerWithin Algorithm method provides a more efficient total inventory cost of Rp. 2.685.821.101 with8 times the frequency of ordering and can savings of 14.8% of total raw material inventory cost.

Impact of TPM implementation on Indian manufacturing industry

2014 ◽  
Vol 63 (1) ◽  
pp. 44-56 ◽  
Author(s):  
Jitendra Kumar ◽  
Vimlesh Kumar Soni ◽  
Geeta Agnihotri
Keyword(s):  
Organizational Performance ◽  
Manufacturing Industry ◽  
Performance Monitoring ◽  
Manufacturing Industries ◽  
Research Approach ◽  
Content Type ◽  
Manufacturing Performance ◽  
The Common ◽  
Manufacturing Productivity ◽  
The Impact

Purpose – The purpose of this paper is to identify the relationship between TPM programme and manufacturing performance in Indian manufacturing industries; to discern the benefits obtained from TPM implementation; to identify common indicators; and to explore the common expectation while TPM implementation. Design/methodology/approach – In this paper acceptability and implementation of TPM programme in Indian manufacturing industry have been elaborated to ascertain the tangible and intangible benefits accrued as a result of successful TPM implementation. A semi-structured questionnaire survey approach has been adopted for the justification of TPM implementation and benefits gained by it in Indian context. Survey has covered mainly automobile and machinery sector throughout India. A total of 57 filled responses have been received and analysed to find the impact of TPM programme on manufacturing productivity. Findings – The paper establishes the impact of successful TPM implementation on manufacturing performance. TPM initiatives have shown marked improvement in the equipment availability, performance and produced quality and have also brought appreciable improvement in other manufacturing functions in the organizations. It has been observed that TPM deployment contributes to improve the manufacturing productivity, quality, delivery, safety, morale, ensuring the cost effectiveness of the manufacturing function within the organization. The paper also indicates that overall equipment effectiveness (OEE) can be used for performance improvement without TPM implementation. Research limitations/implications – Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further. Practical implications – This paper highlights the contribution of TPM programme and OEE measure to ensure enhanced manufacturing productivity. The benefits gained by TPM implementation in selected Indian manufacturing industries have been highlighted, that could be genuine source of motivation to other manufacturing organizations to go in for TPM programme. Originality/value – The present study encompasses systematic identification of factors affecting overall organizational performance and the common expectations of the firms through implementation of TPM programme. TPM initiatives provide regular OEE measure, performance monitoring and improvement, and developing guidelines for achieving enhanced manufacturing productivity.

Evaluating the Effect of Main Factors in Manufacturing Production Line Based on Simulation Experiment

2014 ◽  
Vol 606 ◽  
pp. 199-203 ◽  
Author(s):  
Milad Hatami ◽  
Seyed Mojib Zahraee ◽  
Alireza Khademi ◽  
A. Shahpanah ◽  
Jafri Mohd Rohani
Keyword(s):  
Production Line ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Failure Time ◽  
Service Rate ◽  
Manufacturing Companies ◽  
System Productivity ◽  
High Production Rate ◽  
Need To Evaluate ◽  
High Level

Productivity plays a significant role for most companies in order to measure the efficiency. In reality there is an essential need to evaluate the different factors which increasing productivity and achieving the high level of quality, high production rate , machine utilization. On the other hand, manufacturing companies are striving to sustain their competitiveness by improving productivity and quality of manufacturing industry. So it can be acquired by finding ways to deal with various industrial problems which have affected the productivity of manufacturing systems. This paper aims at applying statistical analysis and computer simulation to recognize and to weight the significance of different factors in the production line. Based on the final result the two factors which are B (Number of labor) and C (Failure time of lifter) have the most significant effect on the manufacturing system productivity. In order to achieve the maximum productivity the factors should be placed on the levels which are: A= -1, B=1, C=1 and D=1. This means that the service rate of mixer = UNIF (20, 40), number of labor=20, failure time of lifter =60 min and number of permil=5 respectively.

scholarly journals An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5480 ◽  
Author(s):  
Panagiotis Trakadas ◽  
Pieter Simoens ◽  
Panagiotis Gkonis ◽  
Lambros Sarakis ◽  
Angelos Angelopoulos ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Business Intelligence ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Shop Floor ◽  
Efficient Production ◽  
Human In The Loop ◽  
Industrial Iot ◽  
Potential Applications

The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. However, these results are currently only used in isolated and dispersed parts of the production process. At the same time, full integration of artificial intelligence (AI) in all parts of manufacturing systems is currently lacking. In this context, the goal of this manuscript is to present a more holistic integration of AI by promoting collaboration. To this end, collaboration is understood as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites. To address these challenges, the proposed architectural approach builds on three technical pillars: (1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms. In addition, system implementation aspects are discussed and potential applications in industrial environments, as well as business impacts, are presented.

scholarly journals Applying the Plan-Do-Check-Act (PDCA) Cycle to Reduce the Defects in the Manufacturing Industry. A Case Study

2018 ◽  
Vol 8 (11) ◽  
pp. 2181 ◽  
Author(s):  
Arturo Realyvásquez-Vargas ◽  
Karina Arredondo-Soto ◽  
Teresa Carrillo-Gutiérrez ◽  
Gustavo Ravelo
Keyword(s):  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Welding Process ◽  
Manufacturing Companies ◽  
Delivery Times ◽  
Pdca Cycle ◽  
Increasing Demand ◽  
Quality Of Products

Defects are considered as one of the wastes in manufacturing systems that negatively affect the delivery times, cost and quality of products leading to manufacturing companies facing a critical situation with the customers and to not comply with the IPC-A-610E standard for the acceptability of electronic components. This is the case is a manufacturing company located in Tijuana, Mexico. Due to an increasing demand on the products manufactured by this company, several defects have been detected in the welding process of electronic boards, as well as in the components named Thru-Holes. It is for this reason that this paper presents a lean manufacturing application case study. The objective of this research is to reduce at least 20% the defects that are generated during the welding process. In addition, it is intended to increase 20% the capacity of three double production lines where electronic boards are processed. As method, the Plan-Do-Check-Act (PDCA) cycle, is applied. The Pareto charts and the flowchart are used as support tools. As results, defects decreased 65%, 79%, and 77% in three analyzed product models. As conclusion, the PDCA cycle, the Pareto charts, and the flowchart are excellent quality tools that help to decrease the number of defective components.

Advanced Cost-Efficient Production Scheduling in Hi-Tech Manufacturing Industry at Test Operation

2011 ◽  
Vol 110-116 ◽  
pp. 3922-3929 ◽  
Author(s):  
Tanaporn Sillapa-Archa ◽  
Phiphlu Thaninthanadech ◽  
Darin Smitasiri
Keyword(s):  
Production Scheduling ◽  
Product Life Cycle ◽  
Manufacturing Industry ◽  
Production Efficiency ◽  
Rapid Change ◽  
Shop Floor ◽  
Efficient Production ◽  
Manufacturing Companies ◽  
Test Operation ◽  
Scheduling Plan

Rapid change in customer demand and aggressive business competition in high technology industry has driven the need for greater performance with lower price product under short product life cycle. This stimulates semiconductor manufacturing companies to pay much more attention to their cost control and production built strategy. Bad performance in shop-floor planning results in huge inventory, poor equipment efficiency, and therefore it would jeopardize the company sustainability. Consequently, the main objectives of an effective production planning intelligence are to maximize company benefits, meet customer expectation and improve production efficiency. This paper presents an algorithm of production loading plan that balances cost, meet customer delivery request and optimize production efficiency by considering all important constrained factors in manufacturing environment, namely test cost per hour, throughput rate, machine capacity and utilization, hardware set up matrix and limitation, the number of change-over and customer delivery date. The analysis is done by comparing the performance outcome with the common scheduling rules. The result of this new planning logic solution is proved to increase the effectiveness of the production scheduling plan based on available resources on hand and complex of constraint. It also decreases human interfere causing error in planning procedure.

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