Management 2022 Paper II 50 marks Compulsory Solve

Q1

(a) A newly constructed house can collapse due to fault in its design. It can also collapse even if it does not have a design fault. The probability that the design of the newly constructed house is faulty is 0·1. The probability that this house collapses if the design is faulty is 0·95, whereas, the probability that the house collapses without any fault in design is 0·45. It is seen that the house has collapsed. What is the probability that it is due to fault in design? (10 marks) (b) Define 'knowledge-based expert system'. Briefly discuss its major applications in business. (10 marks) (c) "The difference between management of manufacturing (goods) and service operations is reducing." Discuss this statement in the light of the fundamental differences existing between goods and service operations. (10 marks) (d) Eleven police personnel were given a test in shooting. Further they were given a month's training and a second test of equal difficulty was conducted at the end of it. The table below contains the marks awarded in the two tests. Do these marks give evidence that the police personnel benefitted from the training? [Test at 5% level of significance] (Relevant table is attached at the end of this Paper) (10 marks) (e) Outline the objectives of 'Material Requirements Planning (MRP)' and explain how an MRP system can achieve these objectives. (10 marks)

हिंदी में प्रश्न पढ़ें

(a) एक नवनिर्मित मकान अपने डाँचे में त्रुटि के कारण ढह सकता है। यह तब भी ढह सकता है जब इसके डाँचे में कोई त्रुटि नहीं होती। नवनिर्मित मकान के डाँचे में त्रुटि है, इसकी प्रायिकता 0·1 है। यह मकान ढहता है यदि डाँचे में त्रुटि है, इसकी प्रायिकता 0·95 है, जबकि डाँचे में बिना किसी त्रुटि के मकान ढहता है, इसकी प्रायिकता 0·45 है। ऐसा देखा जाता है कि मकान ढह गया है। इसकी क्या प्रायिकता है कि डाँचे में त्रुटि ही इसका कारण है? (10 अंक) (b) 'ज्ञान-आधारित विशेषज्ञ प्रणाली' को परिभाषित कीजिए। व्यवसाय में इसके अधिकांश उपयोग की संक्षेप में विवेचना कीजिए। (10 अंक) (c) "विनिर्माण (वस्तुओं) एवं सेवा संचालन के प्रबंध के बीच का अंतर कम हो रहा है।" वस्तुओं एवं सेवा संचालनों के बीच विद्यमान मौलिक अंतरों के प्रकाश में इस कथन की विवेचना कीजिए। (10 अंक) (d) ग्यारह पुलिसकर्मियों को गोली चलाने की एक जाँच दी गई। पुनः इन्हें एक माह का प्रशिक्षण दिया गया और इसके अंत में समान जटिलता की दूसरी जाँच कराई गई। नीचे की तालिका दोनों जाँचों के अंकों को अंतर्विष्ट करती है। क्या ये अंक प्रमाण देते हैं कि प्रशिक्षण से पुलिसकर्मी लाभान्वित हुए? [जाँच 5% सार्थकता स्तर पर] (आवश्यक सारणी इस पत्र के अंत में संलग्न है) (10 अंक) (e) 'सामग्री आवश्यकता योजना (एम० आर० पी०)' के उद्देश्यों को रेखांकित कीजिए एवं स्पष्ट कीजिए कि किस प्रकार एम० आर० पी० प्रणाली इन उद्देश्यों को प्राप्त कर सकती है। (10 अंक)

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Directive word: Solve

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How this answer will be evaluated

Approach

This multi-part question requires solving a probability problem (a), defining and discussing expert systems (b), critically discussing manufacturing-service convergence (c), conducting hypothesis testing (d), and outlining MRP objectives (e). Allocate approximately 15-20% time to each calculation-heavy part (a and d), with remaining time distributed across (b), (c), and (e). Begin with clear problem identification for each sub-part, show all working steps for quantitative portions, and synthesize conceptual discussions with contemporary business illustrations.

Key points expected

  • Part (a): Apply Bayes' theorem correctly — P(Faulty|Collapsed) = [P(Collapsed|Faulty) × P(Faulty)] / P(Collapsed); calculate total probability of collapse and derive final answer ≈ 0.174 or 17.4%
  • Part (b): Define KBES as AI systems emulating human expert decision-making using knowledge base and inference engine; cite applications in medical diagnosis (e.g., AIIMS diagnostic systems), financial credit scoring, and manufacturing quality control
  • Part (c): Discuss IHIP framework (Intangibility, Heterogeneity, Inseparability, Perishability) versus goods' tangibility; analyze convergence through servitization (e.g., Rolls-Royce Power-by-the-Hour) and productization of services (e.g., MakeMyTrip standardization)
  • Part (d): Apply paired t-test — calculate mean difference, standard deviation of differences, t-statistic, and compare with critical t-value (df=10, α=0.05, two-tailed); conclude whether training significantly improved scores
  • Part (e): State MRP objectives (right quantity, right time, right place, optimal inventory, production scheduling); explain how bill of materials, inventory records, and master production schedule achieve these through time-phased netting and planned order releases

Evaluation rubric

DimensionWeightMax marksExcellentAveragePoor
Concept correctness25%12.5All five sub-parts demonstrate mathematically and conceptually accurate solutions: Bayes' theorem correctly applied with proper conditional probability interpretation; KBES definition captures inference engine-knowledge base architecture; IHIP framework accurately distinguished from goods characteristics; paired t-test assumptions verified and calculations precise; MRP objectives aligned with dependent demand logicMost sub-parts correct but with minor errors: Bayes' formula applied with calculation slips; KBES confused with general AI; limited grasp of IHIP dimensions; t-test procedure incomplete; MRP objectives generic without system linkageFundamental conceptual errors: Bayes' theorem misapplied or ignored; KBES equated with database; manufacturing-service differences confused; wrong statistical test chosen or major calculation errors; MRP objectives missing or incorrect
Framework citation20%10Explicitly names and applies relevant frameworks: Bayes' theorem for (a); Buchanan-Smith expert system architecture for (b); Chase-Tansik service operations classification or Fitzsimmons service management framework for (c); paired t-test statistical framework with proper hypothesis formulation for (d); Orlicky's MRP or Vollmann's manufacturing planning and control framework for (e)Frameworks implied but not named, or partially correct: mentions probability rules without Bayes' attribution; describes expert system components without citing Buchanan; discusses service characteristics without IHIP label; conducts test without formal hypothesis statement; describes MRP without Orlicky referenceNo frameworks cited or completely inappropriate frameworks used: uses simple probability without conditional logic; no expert system architecture; random operations management concepts; wrong statistical framework; no MRP methodology
Case / Indian example15%7.5Relevant Indian illustrations for applicable sub-parts: KBES deployment in Indian Railways maintenance or NPCIL reactor diagnostics; servitization examples like Tata Motors Fleet Management or Indian IT services productization; MRP implementation in Indian manufacturing (e.g., Maruti Suzuki, BHEL) or public sector supply chainsGeneric or international examples where Indian cases are possible: Western expert systems cited; multinational servitization without Indian context; MRP described without Indian applicationNo examples provided or irrelevant examples: no business applications for KBES; no convergence illustrations; no MRP implementation cases
Multi-perspective analysis25%12.5For (c), presents balanced argument showing both convergence forces (technology, servitization, customer co-creation) and persistent divergence (intangibility, simultaneity); for (e), discusses MRP limitations (inflexibility, data intensity) alongside benefits; quantitative parts show awareness of assumption sensitivityOne-sided analysis in (c) emphasizing only convergence or only divergence; (e) describes MRP uncritically; quantitative answers mechanically correct without sensitivity considerationNo analytical depth: (c) as assertion without evidence; (e) as list without explanation; quantitative answers as bare calculations without interpretation
Conclusion & recommendation15%7.5Synthesizes across sub-parts where possible: notes how probabilistic reasoning (a) and statistical testing (d) underpin quality management in MRP systems (e); for (c), nuanced verdict on convergence with sector-specific qualifications; clear actionable implications for each applied sub-partSub-part conclusions present but disconnected: answers (a)-(e) as isolated responses without cross-referencing; generic concluding statements without specific implicationsMissing or inadequate conclusions: quantitative answers without interpretation of results; (c) without final position; (e) without implementation caveats

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