Motion and Time Study

Waste in the construction industry has been the subject of several research projects around the world in recent years. Researchers implement different methods to reduce the amount of waste in the construction industry. One of the effective methods for reducing waste is the application of lean approaches. Lean construction is a result of the introduction of a new form of production management. Although lean construction is still evolving, its generic principles, techniques and tools can already be applied. Waste reduction is one of the basic concepts of lean thinking. In general, project managers tend to conceptualize 'waste' as physical construction waste, but lean thinking believes that there are noticeable wastes hidden in construction processes (such as non–value–adding activities and waiting time). We aim at examining the ability of lean construction principles to reduce construction process waste through a case study (reinforcement process). Computer simulation is utilized to reveal the results of lean principles application prior to real implementation. Results show that different kinds of waste in a construction process can be reduced via adopting lean construction principles using computer simulation.

In order to get effective satisfaction level of customer as well as efficient profit margin many business companies tries to improve their productivity through different lean manufacturing techniques. Productivity improvement means to perform the operation in better way and make it a part of flexible process. Therefore to confirm individuals and organization's growth in productivity it is important to accept efficient productivity improvement technique. The important function in any production oriented industry is that the quantity of work must be attained over a period of time in less than predefined budget. Therefore in order to attain the improvement in productivity company have to minimise the either material cost or labour cost or machining process cost. Cost reduction can be done by using Time Study analysis. Therefore this paper addresses the application of time study in order to reduce the labour cost. Hence this paper mainly focuses on overall saving of labour cost by doing Time Study analysis.

Background: The delay in the delivery of laboratory results can be fatal and can even lead to the death of patients. This study was conducted at the clinical laboratory of the University Hospital of Kinshasa (UHK) from October 2020 to April 2021, aimed to evaluate the laboratory tests' turnaround time (TAT) and to identify reasons for delay.

Material and methods: TAT was quantified using a time and motion analysis approach. The evaluation of TAT consisted of comparing the overall intra-lab TAT with the suggested TAT using student t-test at 95% confidence intervals. Brainstorming was the root cause analysis tool used for identifying reasons for delay.

Results: In this study, the laboratory tests' TATs were significantly higher (p < 0.001) comparing to international guidelines (60 minutes) and customers' suggested TAT (120 minutes). Only 0.98% of the samples were reported within 60 minutes of patient reception and 1.47% within 120 minutes, i.e. an outlier rate of 98.5%. Root causes of delay related to Machinery, Management, Manpower, Materials, Method and Milieu.

Conclusion: Because of many reasons, the laboratory is not meeting the established TAT. Preventive and curative measures must be undertaken to reduce the delay and improve the TAT.

Keywords: Time-Motion Analysis, Turnaround Time, Clinical Laboratory, 
Quality Assurance, Value Stream Mapping, Democratic Republic of the Congo

The nascent wave of disruptive competition in the current business environment brought about by the fourth industrial revolution (Fashion 4.0 or Apparel 4.0) is enormous. Therefore, it is important for the apparel industry to be flexible enough to respond quickly to the unstable customers' demand through continuous improvement of their process efficiency and productivity. This study proposed assembly line balancing problem (ALBP) for complex garment assembly line using simulation-based optimization under stochastic task times. The proposed ALBP solution approach aimed at minimizing the cycle time for a given number of workstations with consideration of constraints on number of resources, precedence relations, and resource types. The empirical study was conducted at Southern Range Nyanza Limited (NYTIL) garment facility and a complex trouser assembly line with 69 workstations was considered. The discrete event simulation of the trouser assembly line was developed using Arena simulation software. The local optimal solution was obtained from simulation experiments which was adopted for the optimization process. The OptQuest tool was used to solve a single objective optimization with discrete control values. The results showed that the average throughput increased by 30% for local optimal line balancing and 55% for global optimal line balancing. Consequently, the cycle time reduced by 23% and 36%, respectively.

There have been little empirical evidences available on a time-motion study of medical specialists, the most vital human resources in Thailand. It is important to study the proportions medical specialist’s
workloads working in multiple units in the hospitals for greater visibility of labor distribution and cost consistent with the actual work. The objective of the present study, therefore, was to describe the
proportion of work distribution as well as their working patterns in many tasks of specialists in public hospitals. This would be beneficial for hospital cost allocation criteria.
A purposive sampling was employed to select eight public hospitals consisting of 3 regional hospitals, 3 general hospitals of the Office of Permanent Secretary, and 2 hospitals of the Ministry of Public
Health (with 600 and 1,000 beds). This study collected data from weekly and monthly work schedules and direct interviews with medical specialists. The data were analyzed by descriptive statistics. Overall,
the medical specialists spent 33% to 36% of their time at inpatient department (IPD), followed by 27% to 32% at outpatient department (OPD) and special clinics. In case of medical teachings, the medical
specialists spent no more than 4.7% of their total time, except pediatricians spent the highest 7.0% for teaching. The administrative task took the smallest proportion of no more than 4.0%. The propotion of time of each specialty was: otolaryngologists OPD : OR : IPD : teaching : administrative task = 27.6 : 24.8 : 41.7 : 2.6 : 3.3; ophthalmologists OPD : OR : IPD : teaching : administrative task = 30.8 : 19.2 : 42.0 : 4.6 : 3.4; internist OPD : IPD : ICU : teaching : administrative task = 28.3 : 55.8 : 11.0 : 3.2 : 1.7; pediatricians OPD : IPD : ICU : NICU : teaching : administrative task = 32.6 : 33.8 : 10.4 : 14.3 : 7.0 : 1.9, obstetricians and gynecologists OPD : OR : LR : IPD : teaching : administrative task = 30.4 : 15.3 : 17.4 : 33.1 : 2.7 : 1.1; surgeons OPD : OR : IPD : ICU : teaching : administrative task = 29.1 : 16.6 : 42.1 : 7.3 : 3.7 : 1.2; orthopedic surgeons OPD : OR : IPD : ICU : teaching : administrative task = 17.6 : 19.2 : 52.9 : 6.9 : 2.4 : 1.0; anesthesiologist
OPD : OR : ICU : anesthesia : teaching : administrative task = 2.2 : 45.2 : 13.5 : 34.7 : 1.5 : 2.9. Proportions of work distribution in the present study may be used to assist decision makers in hospital cost allocation criteria and human resource management. Additionally, this methodology can be applied to other personnel who multitask and can be used to estimate the health workforce needs.

Keywords: time-motion study, medical specialist, work distribution, hospital cost allocation

The construction industry includes a large number of specialized areas and disciplines, most of which are based on cyclical processes during the construction phase. With the introduction of the lean construction concept, researchers have begun to apply lean principles to construction processes. The research described in this paper applies lean principles to a construction operation using computer simulation. Simulation makes it possible to evaluate the effects of implementing lean principles into construction processes prior to real world application. A case study of the bricklaying process was conducted to quantify and evaluate the results of applying lean principles. Data required for constructing the simulation model were gathered from the construction site through work and time study techniques. Preliminary results show improvement opportunities exist in the bricklaying process due to a high share of non value-adding work. The results of lean principles implementation also reveal that lean principles can enhance the performance of the bricklaying process through more than 40% productivity improvement.

The nascent wave of disruptive competition in the current business environment brought about by the fourth industrial revolution (Fashion 4.0 or Apparel 4.0) is enormous. Therefore, it is paramount important to apparel industry to be flexible enough to respond quickly to the unstable customers’ demand through continuous improvement of their process efficiency and productivity. This study aims at achieving an optimal trouser assembly line balancing using simulation-based optimization via design of experiment. The empirical study is conducted at Southern Range Nyanza Limited (NYTIL) garment facility and a complex trouser assembly line with 72 operations is considered. The discrete event simulation of the trouser assembly line is developed using Arena simulation software. The local optimal solution is obtained from simulation experimentation and is adopted for the optimization process. The OptQuest tool is utilized to solve a single objective function (throughput) optimization problem. The results show that average throughput increases from the existing design (490 pieces per day) to local optimal design (638) and global optimal design (762). Consequently, the line efficiency increases from 61.2% to 79.7% to 95.2% respectively. The high increase in line efficiency and average throughput confirms the suitability assembly line balancing using simulation-based optimization via design of experiment.